{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S11_S18_farmer_sample.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Apr 2024, 11:02:48
{txt}
{com}. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}      2,325        3.46        3.46
{txt}       2009 {c |}{res}      2,359        3.51        6.97
{txt}       2010 {c |}{res}      9,246       13.75       20.72
{txt}       2011 {c |}{res}      8,192       12.19       32.91
{txt}       2012 {c |}{res}      6,506        9.68       42.59
{txt}       2013 {c |}{res}      7,503       11.16       53.75
{txt}       2014 {c |}{res}      5,153        7.67       61.42
{txt}       2015 {c |}{res}      8,909       13.25       74.67
{txt}       2016 {c |}{res}      2,007        2.99       77.65
{txt}       2018 {c |}{res}      6,254        9.30       86.96
{txt}       2019 {c |}{res}      8,767       13.04      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     67,221      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  
{txt}
{com}. 
. 
. 
. 
. ********************************************************************************
. *                                   S11                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    67,221
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,842

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0304                                         {txt}min = {res}         1
{txt}     between = {res}0.3561                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2738                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 19923.17
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,842} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0492922{col 30}{space 2} .0031513{col 41}{space 1}   15.64{col 50}{space 3}0.000{col 58}{space 4} .0431158{col 71}{space 3} .0554686
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.011623{col 30}{space 2} .0024463{col 41}{space 1}   -4.75{col 50}{space 3}0.000{col 58}{space 4}-.0164177{col 71}{space 3}-.0068283
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0028655{col 30}{space 2} .0278001{col 41}{space 1}   -0.10{col 50}{space 3}0.918{col 58}{space 4}-.0573528{col 71}{space 3} .0516218
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005111{col 30}{space 2}  .000459{col 41}{space 1}    1.11{col 50}{space 3}0.266{col 58}{space 4}-.0003886{col 71}{space 3} .0014107
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0413031{col 30}{space 2} .0167096{col 41}{space 1}    2.47{col 50}{space 3}0.013{col 58}{space 4} .0085529{col 71}{space 3} .0740533
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2880333{col 30}{space 2}   .01456{col 41}{space 1}   19.78{col 50}{space 3}0.000{col 58}{space 4} .2594963{col 71}{space 3} .3165703
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1070704{col 30}{space 2}  .029802{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .0486595{col 71}{space 3} .1654814
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1907612{col 30}{space 2} .0186389{col 41}{space 1}   10.23{col 50}{space 3}0.000{col 58}{space 4} .1542296{col 71}{space 3} .2272929
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1912567{col 30}{space 2} .0228448{col 41}{space 1}    8.37{col 50}{space 3}0.000{col 58}{space 4} .1464817{col 71}{space 3} .2360317
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1373721{col 30}{space 2} .0191447{col 41}{space 1}    7.18{col 50}{space 3}0.000{col 58}{space 4} .0998493{col 71}{space 3}  .174895
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2087156{col 30}{space 2} .0175109{col 41}{space 1}   11.92{col 50}{space 3}0.000{col 58}{space 4} .1743949{col 71}{space 3} .2430363
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0699092{col 30}{space 2} .0134435{col 41}{space 1}   -5.20{col 50}{space 3}0.000{col 58}{space 4} -.096258{col 71}{space 3}-.0435605
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0010639{col 30}{space 2} .0009441{col 41}{space 1}    1.13{col 50}{space 3}0.260{col 58}{space 4}-.0007865{col 71}{space 3} .0029142
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0470482{col 30}{space 2} .0159079{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0158693{col 71}{space 3} .0782271
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .119653{col 30}{space 2} .0401049{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .0410489{col 71}{space 3} .1982572
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5297038{col 30}{space 2} .0272137{col 41}{space 1}   19.46{col 50}{space 3}0.000{col 58}{space 4} .4763659{col 71}{space 3} .5830416
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6181107{col 30}{space 2}  .030943{col 41}{space 1}   19.98{col 50}{space 3}0.000{col 58}{space 4} .5574634{col 71}{space 3} .6787579
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1820221{col 30}{space 2} .0286861{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .1257984{col 71}{space 3} .2382458
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1905879{col 30}{space 2} .0248803{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .1418234{col 71}{space 3} .2393524
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0068534{col 30}{space 2} .0040379{col 41}{space 1}   -1.70{col 50}{space 3}0.090{col 58}{space 4}-.0147676{col 71}{space 3} .0010608
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3248367{col 30}{space 2} .0344283{col 41}{space 1}   -9.44{col 50}{space 3}0.000{col 58}{space 4} -.392315{col 71}{space 3}-.2573585
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2} -1.42301{col 30}{space 2} .0336272{col 41}{space 1}  -42.32{col 50}{space 3}0.000{col 58}{space 4}-1.488918{col 71}{space 3}-1.357102
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} -.347159{col 30}{space 2} .0330263{col 41}{space 1}  -10.51{col 50}{space 3}0.000{col 58}{space 4}-.4118893{col 71}{space 3}-.2824287
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1629399{col 30}{space 2} .0322941{col 41}{space 1}   -5.05{col 50}{space 3}0.000{col 58}{space 4}-.2262352{col 71}{space 3}-.0996445
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .642596{col 30}{space 2} .0382115{col 41}{space 1}   16.82{col 50}{space 3}0.000{col 58}{space 4} .5677029{col 71}{space 3} .7174891
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2341481{col 30}{space 2} .0419632{col 41}{space 1}   -5.58{col 50}{space 3}0.000{col 58}{space 4}-.3163945{col 71}{space 3}-.1519018
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} -.021111{col 30}{space 2} .0310553{col 41}{space 1}   -0.68{col 50}{space 3}0.497{col 58}{space 4}-.0819782{col 71}{space 3} .0397562
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0611729{col 30}{space 2} .0358597{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0091109{col 71}{space 3} .1314566
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0098999{col 30}{space 2} .0315677{col 41}{space 1}    0.31{col 50}{space 3}0.754{col 58}{space 4}-.0519717{col 71}{space 3} .0717714
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1027177{col 30}{space 2}  .035631{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0328822{col 71}{space 3} .1725532
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0961883{col 30}{space 2} .0367779{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4}-.1682717{col 71}{space 3}-.0241048
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1573715{col 30}{space 2} .0347431{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .0892762{col 71}{space 3} .2254667
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2155919{col 30}{space 2} .0475139{col 41}{space 1}   -4.54{col 50}{space 3}0.000{col 58}{space 4}-.3087174{col 71}{space 3}-.1224664
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4508311{col 30}{space 2} .0368725{col 41}{space 1}   12.23{col 50}{space 3}0.000{col 58}{space 4} .3785623{col 71}{space 3} .5230999
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0103237{col 30}{space 2} .0339867{col 41}{space 1}   -0.30{col 50}{space 3}0.761{col 58}{space 4}-.0769363{col 71}{space 3}  .056289
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.479052{col 30}{space 2} .0515594{col 41}{space 1}   86.87{col 50}{space 3}0.000{col 58}{space 4} 4.377997{col 71}{space 3} 4.580106
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78942359
         {txt}sigma_e {c |} {res} 1.2293182
             {txt}rho {c |} {res} .29197238{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,981
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,826

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0194                                         {txt}min = {res}         1
{txt}     between = {res}0.3003                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.1936                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1720.70
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,826} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0170797{col 30}{space 2}  .005886{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0055433{col 71}{space 3} .0286161
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0355519{col 30}{space 2} .0076512{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4} .0205557{col 71}{space 3} .0505481
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0115275{col 30}{space 2} .0625206{col 41}{space 1}    0.18{col 50}{space 3}0.854{col 58}{space 4}-.1110107{col 71}{space 3} .1340657
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028057{col 30}{space 2} .0010725{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4}-.0049078{col 71}{space 3}-.0007035
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0015073{col 30}{space 2} .0391528{col 41}{space 1}    0.04{col 50}{space 3}0.969{col 58}{space 4}-.0752308{col 71}{space 3} .0782455
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3307477{col 30}{space 2} .0323142{col 41}{space 1}   10.24{col 50}{space 3}0.000{col 58}{space 4} .2674131{col 71}{space 3} .3940823
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1992475{col 30}{space 2} .1608036{col 41}{space 1}   -1.24{col 50}{space 3}0.215{col 58}{space 4}-.5144168{col 71}{space 3} .1159218
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1798178{col 30}{space 2} .0382608{col 41}{space 1}    4.70{col 50}{space 3}0.000{col 58}{space 4}  .104828{col 71}{space 3} .2548077
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1558779{col 30}{space 2} .0477324{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0623242{col 71}{space 3} .2494316
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .118356{col 30}{space 2}  .071264{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4} -.021319{col 71}{space 3} .2580309
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2046529{col 30}{space 2} .0523269{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4}  .102094{col 71}{space 3} .3072118
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1571409{col 30}{space 2} .0299139{col 41}{space 1}   -5.25{col 50}{space 3}0.000{col 58}{space 4}-.2157711{col 71}{space 3}-.0985107
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0101041{col 30}{space 2}  .003752{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0027502{col 71}{space 3}  .017458
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2320815{col 30}{space 2} .0335399{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4} .1663445{col 71}{space 3} .2978185
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9003759{col 30}{space 2} .2817322{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4}  .348191{col 71}{space 3} 1.452561
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4198993{col 30}{space 2} .0597926{col 41}{space 1}    7.02{col 50}{space 3}0.000{col 58}{space 4}  .302708{col 71}{space 3} .5370907
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4011839{col 30}{space 2} .0719503{col 41}{space 1}    5.58{col 50}{space 3}0.000{col 58}{space 4} .2601639{col 71}{space 3} .5422039
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .358326{col 30}{space 2} .1152716{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4} .1323978{col 71}{space 3} .5842542
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1370425{col 30}{space 2} .0669651{col 41}{space 1}    2.05{col 50}{space 3}0.041{col 58}{space 4} .0057934{col 71}{space 3} .2682916
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0249156{col 30}{space 2}  .007521{col 41}{space 1}    3.31{col 50}{space 3}0.001{col 58}{space 4} .0101748{col 71}{space 3} .0396565
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1751012{col 30}{space 2} .0236739{col 41}{space 1}   -7.40{col 50}{space 3}0.000{col 58}{space 4}-.2215013{col 71}{space 3}-.1287012
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.160042{col 30}{space 2} .0787098{col 41}{space 1}   40.15{col 50}{space 3}0.000{col 58}{space 4} 3.005774{col 71}{space 3}  3.31431
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .71471476
         {txt}sigma_e {c |} {res} 1.0547888
             {txt}rho {c |} {res} .31465951{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,359
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0445                                         {txt}min = {res}         1
{txt}     between = {res}0.3468                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2622                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2233.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0951752{col 30}{space 2} .0109165{col 41}{space 1}    8.72{col 50}{space 3}0.000{col 58}{space 4} .0737792{col 71}{space 3} .1165712
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0154649{col 30}{space 2} .0095376{col 41}{space 1}   -1.62{col 50}{space 3}0.105{col 58}{space 4}-.0341583{col 71}{space 3} .0032285
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2884025{col 30}{space 2} .0838579{col 41}{space 1}   -3.44{col 50}{space 3}0.001{col 58}{space 4} -.452761{col 71}{space 3}-.1240441
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0034857{col 30}{space 2} .0013473{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.0061263{col 71}{space 3}-.0008451
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0906904{col 30}{space 2} .0463369{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.1815092{col 71}{space 3} .0001283
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2824786{col 30}{space 2} .0472497{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .1898709{col 71}{space 3} .3750863
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3557254{col 30}{space 2} .1569058{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0481957{col 71}{space 3} .6632551
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2250854{col 30}{space 2} .0563316{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .1146774{col 71}{space 3} .3354934
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4155859{col 30}{space 2}  .115251{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .1896981{col 71}{space 3} .6414736
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1499377{col 30}{space 2} .0653917{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0217722{col 71}{space 3} .2781032
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}   .26277{col 30}{space 2} .0472062{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .1702476{col 71}{space 3} .3552925
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2007197{col 30}{space 2} .0345843{col 41}{space 1}   -5.80{col 50}{space 3}0.000{col 58}{space 4}-.2685037{col 71}{space 3}-.1329356
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0200623{col 30}{space 2} .0268094{col 41}{space 1}    0.75{col 50}{space 3}0.454{col 58}{space 4}-.0324831{col 71}{space 3} .0726077
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0724293{col 30}{space 2} .0485511{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-.1675877{col 71}{space 3} .0227291
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1236124{col 30}{space 2}  .226283{col 41}{space 1}    0.55{col 50}{space 3}0.585{col 58}{space 4} -.319894{col 71}{space 3} .5671189
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .536919{col 30}{space 2} .0815782{col 41}{space 1}    6.58{col 50}{space 3}0.000{col 58}{space 4} .3770287{col 71}{space 3} .6968094
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7362808{col 30}{space 2} .1428331{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4}  .456333{col 71}{space 3} 1.016229
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4151448{col 30}{space 2} .0914351{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .2359354{col 71}{space 3} .5943542
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3743357{col 30}{space 2} .0746862{col 41}{space 1}    5.01{col 50}{space 3}0.000{col 58}{space 4} .2279534{col 71}{space 3} .5207179
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0312878{col 30}{space 2} .0159301{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.0625102{col 71}{space 3}-.0000654
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1656909{col 30}{space 2} .0472726{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0730384{col 71}{space 3} .2583434
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0780037{col 30}{space 2} .0398749{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4}-.0001497{col 71}{space 3}  .156157
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.164995{col 30}{space 2} .0990091{col 41}{space 1}   52.17{col 50}{space 3}0.000{col 58}{space 4}  4.97094{col 71}{space 3} 5.359049
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69837948
         {txt}sigma_e {c |} {res} 1.3063755
             {txt}rho {c |} {res} .22226797{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,312
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,179

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0618                                         {txt}min = {res}         1
{txt}     between = {res}0.1767                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1376                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}   891.49
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,179} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1562085{col 30}{space 2}   .01897{col 41}{space 1}    8.23{col 50}{space 3}0.000{col 58}{space 4}  .119028{col 71}{space 3}  .193389
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0092795{col 30}{space 2} .0073668{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.0051591{col 71}{space 3} .0237182
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0929792{col 30}{space 2} .1164553{col 41}{space 1}   -0.80{col 50}{space 3}0.425{col 58}{space 4}-.3212275{col 71}{space 3} .1352691
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0033546{col 30}{space 2} .0015636{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4}   .00029{col 71}{space 3} .0064191
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0827874{col 30}{space 2} .0699224{col 41}{space 1}    1.18{col 50}{space 3}0.236{col 58}{space 4} -.054258{col 71}{space 3} .2198327
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2886079{col 30}{space 2} .0512203{col 41}{space 1}    5.63{col 50}{space 3}0.000{col 58}{space 4}  .188218{col 71}{space 3} .3889977
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3905069{col 30}{space 2} .1424037{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .1114008{col 71}{space 3} .6696131
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0427168{col 30}{space 2} .0847822{col 41}{space 1}    0.50{col 50}{space 3}0.614{col 58}{space 4}-.1234534{col 71}{space 3} .2088869
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1898115{col 30}{space 2} .1805144{col 41}{space 1}    1.05{col 50}{space 3}0.293{col 58}{space 4}-.1639903{col 71}{space 3} .5436133
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2447795{col 30}{space 2} .1089918{col 41}{space 1}    2.25{col 50}{space 3}0.025{col 58}{space 4} .0311594{col 71}{space 3} .4583995
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2540091{col 30}{space 2} .0758193{col 41}{space 1}   -3.35{col 50}{space 3}0.001{col 58}{space 4}-.4026123{col 71}{space 3}-.1054059
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.13128{col 30}{space 2} .0460483{col 41}{space 1}   -2.85{col 50}{space 3}0.004{col 58}{space 4} -.221533{col 71}{space 3} -.041027
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014198{col 30}{space 2} .0015736{col 41}{space 1}   -0.90{col 50}{space 3}0.367{col 58}{space 4} -.004504{col 71}{space 3} .0016645
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1776019{col 30}{space 2} .2160241{col 41}{space 1}    0.82{col 50}{space 3}0.411{col 58}{space 4}-.2457975{col 71}{space 3} .6010013
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0133212{col 30}{space 2}  .170121{col 41}{space 1}    0.08{col 50}{space 3}0.938{col 58}{space 4}-.3201098{col 71}{space 3} .3467522
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3491665{col 30}{space 2} .1027255{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .1478281{col 71}{space 3} .5505048
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6694288{col 30}{space 2} .1956101{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .2860401{col 71}{space 3} 1.052818
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0827114{col 30}{space 2} .1347409{col 41}{space 1}    0.61{col 50}{space 3}0.539{col 58}{space 4} -.181376{col 71}{space 3} .3467988
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .542977{col 30}{space 2}  .093142{col 41}{space 1}    5.83{col 50}{space 3}0.000{col 58}{space 4}  .360422{col 71}{space 3} .7255319
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.1353881{col 30}{space 2} .0222643{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4}-.1790253{col 71}{space 3}-.0917509
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2654891{col 30}{space 2}  .043169{col 41}{space 1}    6.15{col 50}{space 3}0.000{col 58}{space 4} .1808794{col 71}{space 3} .3500988
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.424739{col 30}{space 2} .1194064{col 41}{space 1}   37.06{col 50}{space 3}0.000{col 58}{space 4} 4.190707{col 71}{space 3} 4.658771
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54729766
         {txt}sigma_e {c |} {res} 1.4174196
             {txt}rho {c |} {res} .12974662{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,882
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,309

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0382                                         {txt}min = {res}         1
{txt}     between = {res}0.2980                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2528                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3461.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,309} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0535722{col 30}{space 2} .0096913{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .0345775{col 71}{space 3} .0725668
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0300738{col 30}{space 2} .0049975{col 41}{space 1}   -6.02{col 50}{space 3}0.000{col 58}{space 4}-.0398688{col 71}{space 3}-.0202788
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1933464{col 30}{space 2} .0592193{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0772788{col 71}{space 3} .3094141
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .006072{col 30}{space 2} .0010395{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .0040346{col 71}{space 3} .0081094
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3029332{col 30}{space 2}  .043009{col 41}{space 1}    7.04{col 50}{space 3}0.000{col 58}{space 4} .2186371{col 71}{space 3} .3872293
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2061926{col 30}{space 2} .0297482{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4} .1478872{col 71}{space 3}  .264498
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} -.029444{col 30}{space 2} .0451396{col 41}{space 1}   -0.65{col 50}{space 3}0.514{col 58}{space 4}-.1179161{col 71}{space 3}  .059028
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .140682{col 30}{space 2} .0434969{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4} .0554297{col 71}{space 3} .2259343
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .079094{col 30}{space 2} .0556683{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4}-.0300139{col 71}{space 3} .1882019
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2432065{col 30}{space 2} .0662853{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .1132897{col 71}{space 3} .3731233
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3089195{col 30}{space 2} .0471251{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4}  .216556{col 71}{space 3}  .401283
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0574413{col 30}{space 2} .0482911{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0372075{col 71}{space 3}   .15209
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0064452{col 30}{space 2} .0060282{col 41}{space 1}   -1.07{col 50}{space 3}0.285{col 58}{space 4}-.0182603{col 71}{space 3}   .00537
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3300877{col 30}{space 2} .0610993{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2103352{col 71}{space 3} .4498401
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1622944{col 30}{space 2} .0601101{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0444808{col 71}{space 3} .2801081
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7486991{col 30}{space 2}  .063689{col 41}{space 1}   11.76{col 50}{space 3}0.000{col 58}{space 4}  .623871{col 71}{space 3} .8735271
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7943675{col 30}{space 2} .0676239{col 41}{space 1}   11.75{col 50}{space 3}0.000{col 58}{space 4}  .661827{col 71}{space 3} .9269079
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0911619{col 30}{space 2} .0843377{col 41}{space 1}    1.08{col 50}{space 3}0.280{col 58}{space 4}-.0741369{col 71}{space 3} .2564606
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0378291{col 30}{space 2} .0594034{col 41}{space 1}   -0.64{col 50}{space 3}0.524{col 58}{space 4}-.1542577{col 71}{space 3} .0785994
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0882676{col 30}{space 2} .0127651{col 41}{space 1}   -6.91{col 50}{space 3}0.000{col 58}{space 4}-.1132867{col 71}{space 3}-.0632485
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5446515{col 30}{space 2}  .036085{col 41}{space 1}  -15.09{col 50}{space 3}0.000{col 58}{space 4}-.6153768{col 71}{space 3}-.4739263
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5258457{col 30}{space 2} .0366411{col 41}{space 1}  -14.35{col 50}{space 3}0.000{col 58}{space 4}-.5976609{col 71}{space 3}-.4540306
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3527111{col 30}{space 2} .0361776{col 41}{space 1}   -9.75{col 50}{space 3}0.000{col 58}{space 4}-.4236179{col 71}{space 3}-.2818042
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.666175{col 30}{space 2} .0852266{col 41}{space 1}   54.75{col 50}{space 3}0.000{col 58}{space 4} 4.499134{col 71}{space 3} 4.833216
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85034737
         {txt}sigma_e {c |} {res} 1.2181283
             {txt}rho {c |} {res} .32764588{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,921
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,358

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0289                                         {txt}min = {res}         1
{txt}     between = {res}0.2314                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1859                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2692.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,358} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0655982{col 30}{space 2} .0060455{col 41}{space 1}   10.85{col 50}{space 3}0.000{col 58}{space 4} .0537492{col 71}{space 3} .0774472
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0158986{col 30}{space 2} .0046027{col 41}{space 1}   -3.45{col 50}{space 3}0.001{col 58}{space 4}-.0249198{col 71}{space 3}-.0068775
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0437211{col 30}{space 2}  .058013{col 41}{space 1}   -0.75{col 50}{space 3}0.451{col 58}{space 4}-.1574246{col 71}{space 3} .0699824
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020318{col 30}{space 2} .0009328{col 41}{space 1}   -2.18{col 50}{space 3}0.029{col 58}{space 4}-.0038601{col 71}{space 3}-.0002036
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0288083{col 30}{space 2} .0331185{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.0361027{col 71}{space 3} .0937193
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2715078{col 30}{space 2} .0307757{col 41}{space 1}    8.82{col 50}{space 3}0.000{col 58}{space 4} .2111885{col 71}{space 3} .3318271
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1935015{col 30}{space 2} .0746101{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0472683{col 71}{space 3} .3397347
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2898512{col 30}{space 2} .0425696{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .2064164{col 71}{space 3} .3732861
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1147347{col 30}{space 2}  .049476{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0177634{col 71}{space 3} .2117059
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1481044{col 30}{space 2} .0335602{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0823275{col 71}{space 3} .2138812
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2319787{col 30}{space 2} .0359254{col 41}{space 1}    6.46{col 50}{space 3}0.000{col 58}{space 4} .1615663{col 71}{space 3} .3023911
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1585746{col 30}{space 2} .0297552{col 41}{space 1}   -5.33{col 50}{space 3}0.000{col 58}{space 4}-.2168938{col 71}{space 3}-.1002554
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0033554{col 30}{space 2} .0018643{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0002986{col 71}{space 3} .0070093
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0717776{col 30}{space 2} .0305357{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.1316264{col 71}{space 3}-.0119288
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4226216{col 30}{space 2} .0960476{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .2343718{col 71}{space 3} .6108714
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4165739{col 30}{space 2} .0578485{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4}  .303193{col 71}{space 3} .5299548
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4769639{col 30}{space 2} .0640897{col 41}{space 1}    7.44{col 50}{space 3}0.000{col 58}{space 4} .3513505{col 71}{space 3} .6025774
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .057973{col 30}{space 2} .0481542{col 41}{space 1}    1.20{col 50}{space 3}0.229{col 58}{space 4}-.0364074{col 71}{space 3} .1523534
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2491729{col 30}{space 2}  .050019{col 41}{space 1}    4.98{col 50}{space 3}0.000{col 58}{space 4} .1511376{col 71}{space 3} .3472082
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0173927{col 30}{space 2} .0073163{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.0317323{col 71}{space 3}-.0030531
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0408254{col 30}{space 2} .0327797{col 41}{space 1}    1.25{col 50}{space 3}0.213{col 58}{space 4}-.0234216{col 71}{space 3} .1050724
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0710906{col 30}{space 2} .0274148{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0173586{col 71}{space 3} .1248227
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}  .032715{col 30}{space 2} .0330331{col 41}{space 1}    0.99{col 50}{space 3}0.322{col 58}{space 4}-.0320288{col 71}{space 3} .0974588
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.513052{col 30}{space 2} .0699948{col 41}{space 1}   64.48{col 50}{space 3}0.000{col 58}{space 4} 4.375864{col 71}{space 3} 4.650239
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76064145
         {txt}sigma_e {c |} {res} 1.2054923
             {txt}rho {c |} {res} .28476183{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,766
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0500                                         {txt}min = {res}         1
{txt}     between = {res}0.2925                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1840                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2514.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0535096{col 30}{space 2} .0061722{col 41}{space 1}    8.67{col 50}{space 3}0.000{col 58}{space 4} .0414123{col 71}{space 3} .0656069
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0035035{col 30}{space 2} .0054472{col 41}{space 1}    0.64{col 50}{space 3}0.520{col 58}{space 4}-.0071728{col 71}{space 3} .0141798
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0247823{col 30}{space 2} .0582317{col 41}{space 1}    0.43{col 50}{space 3}0.670{col 58}{space 4}-.0893497{col 71}{space 3} .1389143
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003626{col 30}{space 2} .0010327{col 41}{space 1}   -0.35{col 50}{space 3}0.726{col 58}{space 4}-.0023867{col 71}{space 3} .0016615
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0612409{col 30}{space 2} .0332538{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0039354{col 71}{space 3} .1264172
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3136751{col 30}{space 2} .0329723{col 41}{space 1}    9.51{col 50}{space 3}0.000{col 58}{space 4} .2490507{col 71}{space 3} .3782996
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2156946{col 30}{space 2} .0535695{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} .1107004{col 71}{space 3} .3206888
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2371037{col 30}{space 2}  .035096{col 41}{space 1}    6.76{col 50}{space 3}0.000{col 58}{space 4} .1683169{col 71}{space 3} .3058905
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3746983{col 30}{space 2} .0365433{col 41}{space 1}   10.25{col 50}{space 3}0.000{col 58}{space 4} .3030746{col 71}{space 3} .4463219
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0508945{col 30}{space 2} .0292953{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0065233{col 71}{space 3} .1083123
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .184142{col 30}{space 2} .0301402{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4} .1250682{col 71}{space 3} .2432157
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0070236{col 30}{space 2} .0237872{col 41}{space 1}   -0.30{col 50}{space 3}0.768{col 58}{space 4}-.0536458{col 71}{space 3} .0395985
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0017584{col 30}{space 2}  .001195{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0005837{col 71}{space 3} .0041005
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0646304{col 30}{space 2} .0278143{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4}-.1191454{col 71}{space 3}-.0101154
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1709434{col 30}{space 2} .0836818{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4}   .00693{col 71}{space 3} .3349568
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .386116{col 30}{space 2}  .060852{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .2668483{col 71}{space 3} .5053838
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3314146{col 30}{space 2} .0685181{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .1971215{col 71}{space 3} .4657077
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1748546{col 30}{space 2} .0556352{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0658117{col 71}{space 3} .2838975
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2979756{col 30}{space 2} .0535602{col 41}{space 1}    5.56{col 50}{space 3}0.000{col 58}{space 4} .1929996{col 71}{space 3} .4029516
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0268726{col 30}{space 2} .0094831{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0082861{col 71}{space 3} .0454591
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2164236{col 30}{space 2} .0350773{col 41}{space 1}   -6.17{col 50}{space 3}0.000{col 58}{space 4} -.285174{col 71}{space 3}-.1476733
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0914255{col 30}{space 2} .0332099{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.1565157{col 71}{space 3}-.0263352
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3714924{col 30}{space 2} .0326197{col 41}{space 1}   11.39{col 50}{space 3}0.000{col 58}{space 4}  .307559{col 71}{space 3} .4354257
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1088472{col 30}{space 2} .0327867{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0445864{col 71}{space 3}  .173108
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3352034{col 30}{space 2} .0305982{col 41}{space 1}   10.95{col 50}{space 3}0.000{col 58}{space 4}  .275232{col 71}{space 3} .3951748
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.902969{col 30}{space 2} .0860929{col 41}{space 1}   45.33{col 50}{space 3}0.000{col 58}{space 4}  3.73423{col 71}{space 3} 4.071708
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .77292846
         {txt}sigma_e {c |} {res} 1.2466293
             {txt}rho {c |} {res} .27767491{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S11_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean _cons)
{res}{txt}(note: file S11_farmer.rtf not found)
(output written to {browse  `"S11_farmer.rtf"'})

{com}. 
. 
. 
. 
. ********************************************************************************
. *                                   S12                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    67,221
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,842

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0336                                         {txt}min = {res}         1
{txt}     between = {res}0.3608                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2794                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 20850.19
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,842} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1196519{col 30}{space 2} .0060424{col 41}{space 1}   19.80{col 50}{space 3}0.000{col 58}{space 4} .1078089{col 71}{space 3} .1314948
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0133622{col 30}{space 2} .0024252{col 41}{space 1}   -5.51{col 50}{space 3}0.000{col 58}{space 4}-.0181155{col 71}{space 3}-.0086089
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0082417{col 30}{space 2} .0276957{col 41}{space 1}   -0.30{col 50}{space 3}0.766{col 58}{space 4}-.0625242{col 71}{space 3} .0460408
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004152{col 30}{space 2} .0004551{col 41}{space 1}    0.91{col 50}{space 3}0.362{col 58}{space 4}-.0004768{col 71}{space 3} .0013071
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0423232{col 30}{space 2} .0165881{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} .0098112{col 71}{space 3} .0748353
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2837266{col 30}{space 2} .0144907{col 41}{space 1}   19.58{col 50}{space 3}0.000{col 58}{space 4} .2553253{col 71}{space 3} .3121279
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1078579{col 30}{space 2} .0297392{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4}   .04957{col 71}{space 3} .1661457
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1889082{col 30}{space 2} .0186153{col 41}{space 1}   10.15{col 50}{space 3}0.000{col 58}{space 4} .1524229{col 71}{space 3} .2253934
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1840243{col 30}{space 2} .0228204{col 41}{space 1}    8.06{col 50}{space 3}0.000{col 58}{space 4} .1392971{col 71}{space 3} .2287515
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1372757{col 30}{space 2} .0191014{col 41}{space 1}    7.19{col 50}{space 3}0.000{col 58}{space 4} .0998377{col 71}{space 3} .1747137
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2088522{col 30}{space 2} .0174658{col 41}{space 1}   11.96{col 50}{space 3}0.000{col 58}{space 4} .1746198{col 71}{space 3} .2430846
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0721085{col 30}{space 2} .0134042{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}-.0983801{col 71}{space 3}-.0458368
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0007298{col 30}{space 2} .0009482{col 41}{space 1}    0.77{col 50}{space 3}0.442{col 58}{space 4}-.0011286{col 71}{space 3} .0025882
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0868655{col 30}{space 2} .0149235{col 41}{space 1}    5.82{col 50}{space 3}0.000{col 58}{space 4}  .057616{col 71}{space 3}  .116115
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1138528{col 30}{space 2} .0400562{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0353441{col 71}{space 3} .1923614
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5244829{col 30}{space 2} .0271291{col 41}{space 1}   19.33{col 50}{space 3}0.000{col 58}{space 4} .4713108{col 71}{space 3}  .577655
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6400642{col 30}{space 2} .0308431{col 41}{space 1}   20.75{col 50}{space 3}0.000{col 58}{space 4} .5796129{col 71}{space 3} .7005156
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1925274{col 30}{space 2} .0286123{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1364483{col 71}{space 3} .2486066
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1957749{col 30}{space 2} .0247882{col 41}{space 1}    7.90{col 50}{space 3}0.000{col 58}{space 4} .1471909{col 71}{space 3}  .244359
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0082406{col 30}{space 2} .0084416{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0083046{col 71}{space 3} .0247858
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3548979{col 30}{space 2} .0343445{col 41}{space 1}  -10.33{col 50}{space 3}0.000{col 58}{space 4} -.422212{col 71}{space 3}-.2875838
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.496676{col 30}{space 2} .0335492{col 41}{space 1}  -44.61{col 50}{space 3}0.000{col 58}{space 4}-1.562431{col 71}{space 3}-1.430921
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4469593{col 30}{space 2} .0334044{col 41}{space 1}  -13.38{col 50}{space 3}0.000{col 58}{space 4}-.5124307{col 71}{space 3}-.3814878
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2566383{col 30}{space 2} .0327451{col 41}{space 1}   -7.84{col 50}{space 3}0.000{col 58}{space 4}-.3208176{col 71}{space 3}-.1924589
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .5301211{col 30}{space 2} .0384343{col 41}{space 1}   13.79{col 50}{space 3}0.000{col 58}{space 4} .4547913{col 71}{space 3}  .605451
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1730437{col 30}{space 2} .0419497{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.2552637{col 71}{space 3}-.0908238
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0154254{col 30}{space 2} .0310164{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.0453656{col 71}{space 3} .0762165
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0852021{col 30}{space 2} .0358091{col 41}{space 1}    2.38{col 50}{space 3}0.017{col 58}{space 4} .0150175{col 71}{space 3} .1553867
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0387789{col 30}{space 2} .0315629{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.0230833{col 71}{space 3}  .100641
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1259407{col 30}{space 2} .0355227{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0563175{col 71}{space 3} .1955638
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0807232{col 30}{space 2} .0366749{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.1526046{col 71}{space 3}-.0088417
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1786233{col 30}{space 2} .0346898{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4} .1106326{col 71}{space 3}  .246614
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1743035{col 30}{space 2} .0476318{col 41}{space 1}   -3.66{col 50}{space 3}0.000{col 58}{space 4}-.2676602{col 71}{space 3}-.0809468
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4689229{col 30}{space 2} .0368143{col 41}{space 1}   12.74{col 50}{space 3}0.000{col 58}{space 4} .3967683{col 71}{space 3} .5410776
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}  .012778{col 30}{space 2} .0339197{col 41}{space 1}    0.38{col 50}{space 3}0.706{col 58}{space 4}-.0537034{col 71}{space 3} .0792593
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.351048{col 30}{space 2} .0519766{col 41}{space 1}   83.71{col 50}{space 3}0.000{col 58}{space 4} 4.249176{col 71}{space 3} 4.452921
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78460452
         {txt}sigma_e {c |} {res} 1.2274498
             {txt}rho {c |} {res} .29007326{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,981
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,826

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0224                                         {txt}min = {res}         1
{txt}     between = {res}0.3115                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2061                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1902.36
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,826} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .059176{col 30}{space 2} .0115488{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .0365407{col 71}{space 3} .0818112
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0295382{col 30}{space 2} .0075761{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0146895{col 71}{space 3}  .044387
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0036032{col 30}{space 2}  .062034{col 41}{space 1}    0.06{col 50}{space 3}0.954{col 58}{space 4}-.1179813{col 71}{space 3} .1251876
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025189{col 30}{space 2} .0010586{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.0045937{col 71}{space 3}-.0004442
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .006581{col 30}{space 2} .0386868{col 41}{space 1}    0.17{col 50}{space 3}0.865{col 58}{space 4}-.0692437{col 71}{space 3} .0824057
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3204579{col 30}{space 2} .0320207{col 41}{space 1}   10.01{col 50}{space 3}0.000{col 58}{space 4} .2576985{col 71}{space 3} .3832173
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2186138{col 30}{space 2} .1614761{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.5351011{col 71}{space 3} .0978736
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1763789{col 30}{space 2} .0381453{col 41}{space 1}    4.62{col 50}{space 3}0.000{col 58}{space 4} .1016155{col 71}{space 3} .2511424
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1462532{col 30}{space 2} .0476617{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .0528379{col 71}{space 3} .2396685
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1201881{col 30}{space 2} .0710978{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4} -.019161{col 71}{space 3} .2595372
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2092492{col 30}{space 2} .0522262{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .1068876{col 71}{space 3} .3116107
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1484939{col 30}{space 2} .0298423{col 41}{space 1}   -4.98{col 50}{space 3}0.000{col 58}{space 4}-.2069838{col 71}{space 3} -.090004
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0081899{col 30}{space 2} .0036923{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0009532{col 71}{space 3} .0154267
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2118868{col 30}{space 2}  .031252{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4}  .150634{col 71}{space 3} .2731396
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9253929{col 30}{space 2}   .28702{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .3628441{col 71}{space 3} 1.487942
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4269722{col 30}{space 2} .0593178{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4} .3107115{col 71}{space 3}  .543233
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4526979{col 30}{space 2}  .071591{col 41}{space 1}    6.32{col 50}{space 3}0.000{col 58}{space 4} .3123821{col 71}{space 3} .5930137
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .409338{col 30}{space 2} .1153263{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .1833026{col 71}{space 3} .6353733
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1294018{col 30}{space 2} .0667842{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0014929{col 71}{space 3} .2602964
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0901066{col 30}{space 2}  .016296{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4}  .058167{col 71}{space 3} .1220463
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} -.173192{col 30}{space 2} .0230107{col 41}{space 1}   -7.53{col 50}{space 3}0.000{col 58}{space 4}-.2182922{col 71}{space 3}-.1280919
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.919541{col 30}{space 2} .0815555{col 41}{space 1}   35.80{col 50}{space 3}0.000{col 58}{space 4} 2.759695{col 71}{space 3} 3.079387
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70498724
         {txt}sigma_e {c |} {res} 1.0538223
             {txt}rho {c |} {res} .30917079{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,359
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0423                                         {txt}min = {res}         1
{txt}     between = {res}0.3470                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2616                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2212.25
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1274471{col 30}{space 2} .0165182{col 41}{space 1}    7.72{col 50}{space 3}0.000{col 58}{space 4}  .095072{col 71}{space 3} .1598221
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0163189{col 30}{space 2} .0095223{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.0349822{col 71}{space 3} .0023444
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2957132{col 30}{space 2} .0839897{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}  -.46033{col 71}{space 3}-.1310963
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0034767{col 30}{space 2} .0013411{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.0061052{col 71}{space 3}-.0008482
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0914665{col 30}{space 2} .0463197{col 41}{space 1}   -1.97{col 50}{space 3}0.048{col 58}{space 4}-.1822513{col 71}{space 3}-.0006816
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2756167{col 30}{space 2} .0471893{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .1831273{col 71}{space 3}  .368106
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3748942{col 30}{space 2} .1569555{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0672669{col 71}{space 3} .6825214
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2276052{col 30}{space 2} .0565854{col 41}{space 1}    4.02{col 50}{space 3}0.000{col 58}{space 4} .1166999{col 71}{space 3} .3385106
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4204185{col 30}{space 2} .1149731{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .1950753{col 71}{space 3} .6457617
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1420871{col 30}{space 2} .0654512{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0138051{col 71}{space 3} .2703691
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}    .2625{col 30}{space 2} .0471977{col 41}{space 1}    5.56{col 50}{space 3}0.000{col 58}{space 4} .1699942{col 71}{space 3} .3550059
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2020117{col 30}{space 2}  .034581{col 41}{space 1}   -5.84{col 50}{space 3}0.000{col 58}{space 4}-.2697892{col 71}{space 3}-.1342342
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0293397{col 30}{space 2} .0267171{col 41}{space 1}    1.10{col 50}{space 3}0.272{col 58}{space 4} -.023025{col 71}{space 3} .0817043
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0250166{col 30}{space 2}  .047346{col 41}{space 1}    0.53{col 50}{space 3}0.597{col 58}{space 4}-.0677798{col 71}{space 3} .1178129
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1156135{col 30}{space 2} .2264736{col 41}{space 1}    0.51{col 50}{space 3}0.610{col 58}{space 4}-.3282667{col 71}{space 3} .5594937
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .520823{col 30}{space 2} .0819676{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .3601695{col 71}{space 3} .6814765
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7631975{col 30}{space 2} .1434467{col 41}{space 1}    5.32{col 50}{space 3}0.000{col 58}{space 4} .4820471{col 71}{space 3} 1.044348
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4195402{col 30}{space 2} .0913197{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4} .2405568{col 71}{space 3} .5985235
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3758474{col 30}{space 2}  .074608{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .2296183{col 71}{space 3} .5220764
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0187509{col 30}{space 2} .0262995{col 41}{space 1}   -0.71{col 50}{space 3}0.476{col 58}{space 4} -.070297{col 71}{space 3} .0327951
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1625987{col 30}{space 2}  .047155{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0701766{col 71}{space 3} .2550207
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0983647{col 30}{space 2} .0397409{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4}  .020474{col 71}{space 3} .1762554
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.076752{col 30}{space 2} .1043617{col 41}{space 1}   48.65{col 50}{space 3}0.000{col 58}{space 4} 4.872207{col 71}{space 3} 5.281297
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69637648
         {txt}sigma_e {c |} {res} 1.3075702
             {txt}rho {c |} {res}  .2209617{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,312
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,179

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0549                                         {txt}min = {res}         1
{txt}     between = {res}0.1771                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1367                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}   889.00
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,179} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .286459{col 30}{space 2} .0396523{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4}  .208742{col 71}{space 3}  .364176
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0089205{col 30}{space 2}  .007292{col 41}{space 1}    1.22{col 50}{space 3}0.221{col 58}{space 4}-.0053714{col 71}{space 3} .0232125
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0893474{col 30}{space 2} .1161616{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}  -.31702{col 71}{space 3} .1383252
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0034938{col 30}{space 2} .0015591{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0004379{col 71}{space 3} .0065496
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0942334{col 30}{space 2} .0694053{col 41}{space 1}    1.36{col 50}{space 3}0.175{col 58}{space 4}-.0417985{col 71}{space 3} .2302653
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .296241{col 30}{space 2} .0511321{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1960239{col 71}{space 3} .3964582
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3741532{col 30}{space 2} .1414823{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0968531{col 71}{space 3} .6514534
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0517338{col 30}{space 2}  .085365{col 41}{space 1}    0.61{col 50}{space 3}0.544{col 58}{space 4}-.1155784{col 71}{space 3}  .219046
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2105722{col 30}{space 2} .1767676{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4} -.135886{col 71}{space 3} .5570304
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .269163{col 30}{space 2} .1071169{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0592176{col 71}{space 3} .4791083
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2278422{col 30}{space 2} .0759139{col 41}{space 1}   -3.00{col 50}{space 3}0.003{col 58}{space 4}-.3766308{col 71}{space 3}-.0790537
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1341334{col 30}{space 2} .0460228{col 41}{space 1}   -2.91{col 50}{space 3}0.004{col 58}{space 4}-.2243364{col 71}{space 3}-.0439304
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014715{col 30}{space 2} .0015632{col 41}{space 1}   -0.94{col 50}{space 3}0.347{col 58}{space 4}-.0045353{col 71}{space 3} .0015923
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .260105{col 30}{space 2}  .213207{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4} -.157773{col 71}{space 3}  .677983
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0321999{col 30}{space 2} .1698436{col 41}{space 1}    0.19{col 50}{space 3}0.850{col 58}{space 4}-.3006874{col 71}{space 3} .3650872
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3356559{col 30}{space 2} .1032487{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .1332921{col 71}{space 3} .5380197
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6770332{col 30}{space 2} .1919106{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .3008954{col 71}{space 3} 1.053171
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0613236{col 30}{space 2} .1332351{col 41}{space 1}    0.46{col 50}{space 3}0.645{col 58}{space 4}-.1998124{col 71}{space 3} .3224595
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5031921{col 30}{space 2} .0931315{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .3206578{col 71}{space 3} .6857265
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2072913{col 30}{space 2} .0472395{col 41}{space 1}   -4.39{col 50}{space 3}0.000{col 58}{space 4} -.299879{col 71}{space 3}-.1147036
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2905617{col 30}{space 2} .0433834{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .2055318{col 71}{space 3} .3755915
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.304192{col 30}{space 2} .1263998{col 41}{space 1}   34.05{col 50}{space 3}0.000{col 58}{space 4} 4.056452{col 71}{space 3} 4.551931
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .53717096
         {txt}sigma_e {c |} {res} 1.4221859
             {txt}rho {c |} {res} .12485157{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,882
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,309

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.2975                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2537                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3486.61
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,309} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1207056{col 30}{space 2} .0177923{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4} .0858334{col 71}{space 3} .1555778
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  -.03555{col 30}{space 2} .0049331{col 41}{space 1}   -7.21{col 50}{space 3}0.000{col 58}{space 4}-.0452187{col 71}{space 3}-.0258813
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1911576{col 30}{space 2} .0592371{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4}  .075055{col 71}{space 3} .3072603
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0056486{col 30}{space 2} .0010399{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .0036105{col 71}{space 3} .0076868
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3113187{col 30}{space 2} .0427845{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .2274627{col 71}{space 3} .3951747
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1993633{col 30}{space 2} .0297923{col 41}{space 1}    6.69{col 50}{space 3}0.000{col 58}{space 4} .1409715{col 71}{space 3} .2577551
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0209829{col 30}{space 2} .0450628{col 41}{space 1}   -0.47{col 50}{space 3}0.641{col 58}{space 4}-.1093043{col 71}{space 3} .0673385
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1412659{col 30}{space 2} .0435377{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0559336{col 71}{space 3} .2265983
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0762302{col 30}{space 2} .0557693{col 41}{space 1}    1.37{col 50}{space 3}0.172{col 58}{space 4}-.0330757{col 71}{space 3}  .185536
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2477985{col 30}{space 2} .0661942{col 41}{space 1}    3.74{col 50}{space 3}0.000{col 58}{space 4} .1180602{col 71}{space 3} .3775367
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3108063{col 30}{space 2} .0468576{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4}  .218967{col 71}{space 3} .4026455
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0513939{col 30}{space 2} .0482157{col 41}{space 1}    1.07{col 50}{space 3}0.286{col 58}{space 4}-.0431071{col 71}{space 3} .1458949
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0086408{col 30}{space 2} .0068429{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-.0220527{col 71}{space 3} .0047711
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3330088{col 30}{space 2} .0608448{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .2137553{col 71}{space 3} .4522623
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1250422{col 30}{space 2} .0601256{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0071983{col 71}{space 3} .2428861
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7698118{col 30}{space 2} .0635339{col 41}{space 1}   12.12{col 50}{space 3}0.000{col 58}{space 4} .6452876{col 71}{space 3}  .894336
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8410326{col 30}{space 2} .0674777{col 41}{space 1}   12.46{col 50}{space 3}0.000{col 58}{space 4} .7087788{col 71}{space 3} .9732865
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1176765{col 30}{space 2} .0841702{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4} -.047294{col 71}{space 3} .2826471
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0481909{col 30}{space 2} .0590971{col 41}{space 1}   -0.82{col 50}{space 3}0.415{col 58}{space 4} -.164019{col 71}{space 3} .0676372
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0639017{col 30}{space 2} .0242427{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.1114165{col 71}{space 3}-.0163869
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.559572{col 30}{space 2} .0359643{col 41}{space 1}  -15.56{col 50}{space 3}0.000{col 58}{space 4}-.6300608{col 71}{space 3}-.4890833
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5374744{col 30}{space 2} .0364488{col 41}{space 1}  -14.75{col 50}{space 3}0.000{col 58}{space 4}-.6089128{col 71}{space 3}-.4660361
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3653082{col 30}{space 2} .0361434{col 41}{space 1}  -10.11{col 50}{space 3}0.000{col 58}{space 4} -.436148{col 71}{space 3}-.2944684
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.424458{col 30}{space 2} .0874831{col 41}{space 1}   50.58{col 50}{space 3}0.000{col 58}{space 4} 4.252994{col 71}{space 3} 4.595921
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85181744
         {txt}sigma_e {c |} {res} 1.2171973
             {txt}rho {c |} {res} .32874474{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,921
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,358

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0404                                         {txt}min = {res}         1
{txt}     between = {res}0.2353                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1916                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2822.99
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,358} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1813954{col 30}{space 2}  .012513{col 41}{space 1}   14.50{col 50}{space 3}0.000{col 58}{space 4} .1568703{col 71}{space 3} .2059205
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0174076{col 30}{space 2}  .004623{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.0264685{col 71}{space 3}-.0083467
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0518197{col 30}{space 2} .0579862{col 41}{space 1}   -0.89{col 50}{space 3}0.372{col 58}{space 4}-.1654706{col 71}{space 3} .0618312
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0016279{col 30}{space 2}  .000923{col 41}{space 1}   -1.76{col 50}{space 3}0.078{col 58}{space 4}-.0034369{col 71}{space 3} .0001811
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0308953{col 30}{space 2}  .032959{col 41}{space 1}    0.94{col 50}{space 3}0.349{col 58}{space 4}-.0337032{col 71}{space 3} .0954938
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2808334{col 30}{space 2} .0307329{col 41}{space 1}    9.14{col 50}{space 3}0.000{col 58}{space 4} .2205979{col 71}{space 3} .3410688
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1773586{col 30}{space 2} .0737559{col 41}{space 1}    2.40{col 50}{space 3}0.016{col 58}{space 4} .0327997{col 71}{space 3} .3219175
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2784898{col 30}{space 2} .0424003{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1953867{col 71}{space 3} .3615929
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1049567{col 30}{space 2} .0492873{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0083552{col 71}{space 3} .2015581
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1416661{col 30}{space 2} .0333928{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .0762174{col 71}{space 3} .2071148
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2269027{col 30}{space 2} .0357445{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .1568447{col 71}{space 3} .2969607
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1609767{col 30}{space 2} .0296267{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4} -.219044{col 71}{space 3}-.1029094
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0028753{col 30}{space 2} .0018816{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0008126{col 71}{space 3} .0065632
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0117175{col 30}{space 2} .0280236{col 41}{space 1}    0.42{col 50}{space 3}0.676{col 58}{space 4}-.0432078{col 71}{space 3} .0666427
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4420937{col 30}{space 2} .0955768{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .2547667{col 71}{space 3} .6294207
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4264969{col 30}{space 2} .0577081{col 41}{space 1}    7.39{col 50}{space 3}0.000{col 58}{space 4} .3133911{col 71}{space 3} .5396028
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4974098{col 30}{space 2} .0640048{col 41}{space 1}    7.77{col 50}{space 3}0.000{col 58}{space 4} .3719628{col 71}{space 3} .6228569
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0664316{col 30}{space 2}  .047977{col 41}{space 1}    1.38{col 50}{space 3}0.166{col 58}{space 4}-.0276017{col 71}{space 3} .1604648
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2532779{col 30}{space 2} .0498851{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1555049{col 71}{space 3} .3510509
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.068296{col 30}{space 2} .0160418{col 41}{space 1}   -4.26{col 50}{space 3}0.000{col 58}{space 4}-.0997374{col 71}{space 3}-.0368545
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0021928{col 30}{space 2}  .032868{col 41}{space 1}    0.07{col 50}{space 3}0.947{col 58}{space 4}-.0622272{col 71}{space 3} .0666129
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0699844{col 30}{space 2} .0273268{col 41}{space 1}    2.56{col 50}{space 3}0.010{col 58}{space 4} .0164249{col 71}{space 3} .1235439
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0176427{col 30}{space 2} .0327871{col 41}{space 1}    0.54{col 50}{space 3}0.591{col 58}{space 4}-.0466188{col 71}{space 3} .0819043
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.362661{col 30}{space 2} .0734752{col 41}{space 1}   59.38{col 50}{space 3}0.000{col 58}{space 4} 4.218652{col 71}{space 3}  4.50667
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76311967
         {txt}sigma_e {c |} {res} 1.1983283
             {txt}rho {c |} {res} .28852968{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,766
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0520                                         {txt}min = {res}         1
{txt}     between = {res}0.3009                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1912                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2640.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1139041{col 30}{space 2} .0119409{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .0905003{col 71}{space 3}  .137308
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0027248{col 30}{space 2} .0053954{col 41}{space 1}    0.51{col 50}{space 3}0.614{col 58}{space 4}-.0078499{col 71}{space 3} .0132995
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0224806{col 30}{space 2} .0578399{col 41}{space 1}    0.39{col 50}{space 3}0.698{col 58}{space 4}-.0908836{col 71}{space 3} .1358448
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0005101{col 30}{space 2} .0010194{col 41}{space 1}   -0.50{col 50}{space 3}0.617{col 58}{space 4}-.0025081{col 71}{space 3} .0014879
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0646762{col 30}{space 2} .0329766{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0000432{col 71}{space 3} .1293092
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3102108{col 30}{space 2} .0327808{col 41}{space 1}    9.46{col 50}{space 3}0.000{col 58}{space 4} .2459616{col 71}{space 3}   .37446
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .216903{col 30}{space 2} .0534979{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4}  .112049{col 71}{space 3} .3217571
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2346364{col 30}{space 2} .0350479{col 41}{space 1}    6.69{col 50}{space 3}0.000{col 58}{space 4} .1659437{col 71}{space 3}  .303329
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3495978{col 30}{space 2} .0363921{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4} .2782706{col 71}{space 3}  .420925
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0514418{col 30}{space 2} .0293134{col 41}{space 1}    1.75{col 50}{space 3}0.079{col 58}{space 4}-.0060114{col 71}{space 3} .1088951
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1895003{col 30}{space 2} .0301113{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1304832{col 71}{space 3} .2485173
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0024123{col 30}{space 2} .0236447{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.0487551{col 71}{space 3} .0439305
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0020533{col 30}{space 2} .0011814{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0002623{col 71}{space 3} .0043688
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0054767{col 30}{space 2} .0261977{col 41}{space 1}   -0.21{col 50}{space 3}0.834{col 58}{space 4}-.0568233{col 71}{space 3} .0458699
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1600674{col 30}{space 2} .0841073{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0047799{col 71}{space 3} .3249146
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3528421{col 30}{space 2} .0606229{col 41}{space 1}    5.82{col 50}{space 3}0.000{col 58}{space 4} .2340235{col 71}{space 3} .4716608
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3439325{col 30}{space 2} .0682035{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4}  .210256{col 71}{space 3} .4776089
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1914759{col 30}{space 2} .0553558{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .0829805{col 71}{space 3} .2999713
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3213538{col 30}{space 2} .0532606{col 41}{space 1}    6.03{col 50}{space 3}0.000{col 58}{space 4}  .216965{col 71}{space 3} .4257426
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1067866{col 30}{space 2} .0210337{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .0655613{col 71}{space 3}  .148012
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1931391{col 30}{space 2} .0350082{col 41}{space 1}   -5.52{col 50}{space 3}0.000{col 58}{space 4}-.2617538{col 71}{space 3}-.1245243
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1029783{col 30}{space 2} .0333061{col 41}{space 1}   -3.09{col 50}{space 3}0.002{col 58}{space 4} -.168257{col 71}{space 3}-.0376995
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3292662{col 30}{space 2}  .032662{col 41}{space 1}   10.08{col 50}{space 3}0.000{col 58}{space 4} .2652498{col 71}{space 3} .3932826
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0810776{col 30}{space 2} .0327514{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0168861{col 71}{space 3} .1452692
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3111079{col 30}{space 2} .0304016{col 41}{space 1}   10.23{col 50}{space 3}0.000{col 58}{space 4} .2515218{col 71}{space 3} .3706941
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.610974{col 30}{space 2} .0933633{col 41}{space 1}   38.68{col 50}{space 3}0.000{col 58}{space 4} 3.427986{col 71}{space 3} 3.793963
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76515024
         {txt}sigma_e {c |} {res} 1.2453563
             {txt}rho {c |} {res} .27404227{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S12_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S12_farmer.rtf not found)
(output written to {browse  `"S12_farmer.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************  
. *                                 S13_S14                                      *
. ******************************************************************************** 
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(4,932 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    62,289
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    26,569

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0590                                         {txt}min = {res}         1
{txt}     between = {res}0.4342                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.3547                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 27486.01
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:26,569} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1997006{col 30}{space 2} .0062447{col 41}{space 1}   31.98{col 50}{space 3}0.000{col 58}{space 4} .1874612{col 71}{space 3} .2119401
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0225182{col 30}{space 2} .0021769{col 41}{space 1}   10.34{col 50}{space 3}0.000{col 58}{space 4} .0182516{col 71}{space 3} .0267848
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0517776{col 30}{space 2} .0242919{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.0993889{col 71}{space 3}-.0041664
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0012283{col 30}{space 2} .0003929{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0004582{col 71}{space 3} .0019983
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0818552{col 30}{space 2}    .0148{col 41}{space 1}   -5.53{col 50}{space 3}0.000{col 58}{space 4}-.1108627{col 71}{space 3}-.0528477
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0758301{col 30}{space 2} .0127629{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .0508153{col 71}{space 3} .1008449
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0112252{col 30}{space 2} .0270099{col 41}{space 1}   -0.42{col 50}{space 3}0.678{col 58}{space 4}-.0641636{col 71}{space 3} .0417132
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0202883{col 30}{space 2} .0171538{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0133325{col 71}{space 3} .0539091
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0144843{col 30}{space 2} .0227803{col 41}{space 1}   -0.64{col 50}{space 3}0.525{col 58}{space 4}-.0591329{col 71}{space 3} .0301642
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0552981{col 30}{space 2} .0180904{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.0907546{col 71}{space 3}-.0198417
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0296658{col 30}{space 2} .0172113{col 41}{space 1}    1.72{col 50}{space 3}0.085{col 58}{space 4}-.0040677{col 71}{space 3} .0633993
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0283507{col 30}{space 2} .0124692{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4}-.0527899{col 71}{space 3}-.0039116
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0058488{col 30}{space 2} .0010994{col 41}{space 1}    5.32{col 50}{space 3}0.000{col 58}{space 4} .0036939{col 71}{space 3} .0080037
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1738655{col 30}{space 2} .0143266{col 41}{space 1}   12.14{col 50}{space 3}0.000{col 58}{space 4} .1457858{col 71}{space 3} .2019452
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1249094{col 30}{space 2} .0349676{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4} .0563742{col 71}{space 3} .1934447
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0074159{col 30}{space 2} .0237888{col 41}{space 1}    0.31{col 50}{space 3}0.755{col 58}{space 4}-.0392094{col 71}{space 3} .0540412
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1846554{col 30}{space 2} .0288588{col 41}{space 1}   -6.40{col 50}{space 3}0.000{col 58}{space 4}-.2412175{col 71}{space 3}-.1280933
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2254052{col 30}{space 2} .0255845{col 41}{space 1}   -8.81{col 50}{space 3}0.000{col 58}{space 4}-.2755499{col 71}{space 3}-.1752604
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3080118{col 30}{space 2} .0226142{col 41}{space 1}  -13.62{col 50}{space 3}0.000{col 58}{space 4}-.3523348{col 71}{space 3}-.2636888
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3080716{col 30}{space 2} .0080737{col 41}{space 1}   38.16{col 50}{space 3}0.000{col 58}{space 4} .2922474{col 71}{space 3} .3238957
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .4378744{col 30}{space 2} .0265219{col 41}{space 1}   16.51{col 50}{space 3}0.000{col 58}{space 4} .3858925{col 71}{space 3} .4898563
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1841143{col 30}{space 2} .0269626{col 41}{space 1}   -6.83{col 50}{space 3}0.000{col 58}{space 4}-.2369599{col 71}{space 3}-.1312687
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} 1.184978{col 30}{space 2} .0278772{col 41}{space 1}   42.51{col 50}{space 3}0.000{col 58}{space 4}  1.13034{col 71}{space 3} 1.239616
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .7221091{col 30}{space 2} .0258273{col 41}{space 1}   27.96{col 50}{space 3}0.000{col 58}{space 4} .6714885{col 71}{space 3} .7727297
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .8152302{col 30}{space 2} .0321276{col 41}{space 1}   25.37{col 50}{space 3}0.000{col 58}{space 4} .7522613{col 71}{space 3}  .878199
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2686715{col 30}{space 2} .0409493{col 41}{space 1}   -6.56{col 50}{space 3}0.000{col 58}{space 4}-.3489306{col 71}{space 3}-.1884124
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.1068858{col 30}{space 2} .0305629{col 41}{space 1}   -3.50{col 50}{space 3}0.000{col 58}{space 4} -.166788{col 71}{space 3}-.0469837
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1578873{col 30}{space 2} .0340784{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .0910948{col 71}{space 3} .2246798
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0102304{col 30}{space 2} .0307847{col 41}{space 1}    0.33{col 50}{space 3}0.740{col 58}{space 4}-.0501065{col 71}{space 3} .0705674
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}  .101584{col 30}{space 2} .0351117{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0327663{col 71}{space 3} .1704018
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.190894{col 30}{space 2} .0339113{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.2573591{col 71}{space 3} -.124429
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0877175{col 30}{space 2} .0334198{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4}  .022216{col 71}{space 3} .1532191
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.4506956{col 30}{space 2} .0437664{col 41}{space 1}  -10.30{col 50}{space 3}0.000{col 58}{space 4}-.5364761{col 71}{space 3}-.3649152
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3392741{col 30}{space 2} .0353663{col 41}{space 1}    9.59{col 50}{space 3}0.000{col 58}{space 4} .2699575{col 71}{space 3} .4085907
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1863378{col 30}{space 2} .0357819{col 41}{space 1}   -5.21{col 50}{space 3}0.000{col 58}{space 4} -.256469{col 71}{space 3}-.1162066
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}-.1699427{col 30}{space 2} .0444645{col 41}{space 1}   -3.82{col 50}{space 3}0.000{col 58}{space 4}-.2570916{col 71}{space 3}-.0827939
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51556148
         {txt}sigma_e {c |} {res} 1.1143052
             {txt}rho {c |} {res} .17632321{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,874
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,641

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0266                                         {txt}min = {res}         1
{txt}     between = {res}0.4302                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3177                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2974.68
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,641} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0688129{col 30}{space 2} .0122391{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .0448247{col 71}{space 3} .0928011
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0346079{col 30}{space 2}  .006959{col 41}{space 1}    4.97{col 50}{space 3}0.000{col 58}{space 4} .0209685{col 71}{space 3} .0482473
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.056867{col 30}{space 2} .0550564{col 41}{space 1}   -1.03{col 50}{space 3}0.302{col 58}{space 4}-.1647757{col 71}{space 3} .0510416
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0019238{col 30}{space 2}  .000906{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4}  .000148{col 71}{space 3} .0036996
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1009791{col 30}{space 2} .0337395{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-.1671073{col 71}{space 3}-.0348509
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0881183{col 30}{space 2} .0291557{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0309741{col 71}{space 3} .1452624
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} -.230384{col 30}{space 2} .1771773{col 41}{space 1}   -1.30{col 50}{space 3}0.193{col 58}{space 4}-.5776452{col 71}{space 3} .1168772
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0398429{col 30}{space 2} .0396505{col 41}{space 1}    1.00{col 50}{space 3}0.315{col 58}{space 4}-.0378707{col 71}{space 3} .1175565
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1660574{col 30}{space 2} .0458405{col 41}{space 1}   -3.62{col 50}{space 3}0.000{col 58}{space 4} -.255903{col 71}{space 3}-.0762117
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0111817{col 30}{space 2} .0707293{col 41}{space 1}    0.16{col 50}{space 3}0.874{col 58}{space 4}-.1274452{col 71}{space 3} .1498086
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0230998{col 30}{space 2}  .054395{col 41}{space 1}   -0.42{col 50}{space 3}0.671{col 58}{space 4} -.129712{col 71}{space 3} .0835125
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1628788{col 30}{space 2}  .028238{col 41}{space 1}   -5.77{col 50}{space 3}0.000{col 58}{space 4}-.2182242{col 71}{space 3}-.1075334
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .018292{col 30}{space 2} .0064176{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0057138{col 71}{space 3} .0308703
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0136834{col 30}{space 2} .0278319{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4} -.068233{col 71}{space 3} .0408662
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2819359{col 30}{space 2} .2716464{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.2504812{col 71}{space 3}  .814353
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0939793{col 30}{space 2} .0545992{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4}-.2009918{col 71}{space 3} .0130332
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2562458{col 30}{space 2} .0621188{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.3779965{col 71}{space 3}-.1344952
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3508627{col 30}{space 2} .0987756{col 41}{space 1}   -3.55{col 50}{space 3}0.000{col 58}{space 4}-.5444594{col 71}{space 3} -.157266
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2444208{col 30}{space 2}  .065435{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.3726711{col 71}{space 3}-.1161705
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2803493{col 30}{space 2} .0154699{col 41}{space 1}   18.12{col 50}{space 3}0.000{col 58}{space 4} .2500288{col 71}{space 3} .3106698
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1644646{col 30}{space 2}  .021739{col 41}{space 1}   -7.57{col 50}{space 3}0.000{col 58}{space 4}-.2070722{col 71}{space 3}-.1218569
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5097576{col 30}{space 2} .0675832{col 41}{space 1}    7.54{col 50}{space 3}0.000{col 58}{space 4} .3772969{col 71}{space 3} .6422183
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55437371
         {txt}sigma_e {c |} {res}  .8839549
             {txt}rho {c |} {res} .28228932{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,351
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1469                                         {txt}min = {res}         1
{txt}     between = {res}0.3712                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.3078                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2913.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2786954{col 30}{space 2} .0154798{col 41}{space 1}   18.00{col 50}{space 3}0.000{col 58}{space 4} .2483556{col 71}{space 3} .3090352
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0026751{col 30}{space 2} .0082467{col 41}{space 1}   -0.32{col 50}{space 3}0.746{col 58}{space 4}-.0188383{col 71}{space 3} .0134881
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0949052{col 30}{space 2} .0701111{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.2323205{col 71}{space 3}   .04251
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0034095{col 30}{space 2} .0011796{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0010976{col 71}{space 3} .0057214
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0848162{col 30}{space 2}  .039215{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.1616763{col 71}{space 3}-.0079561
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0698051{col 30}{space 2} .0390118{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0066566{col 71}{space 3} .1462668
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2882633{col 30}{space 2} .1473134{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4}-.0004657{col 71}{space 3} .5769923
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0197582{col 30}{space 2} .0479684{col 41}{space 1}    0.41{col 50}{space 3}0.680{col 58}{space 4}-.0742582{col 71}{space 3} .1137746
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2062972{col 30}{space 2} .1102888{col 41}{space 1}   -1.87{col 50}{space 3}0.061{col 58}{space 4}-.4224594{col 71}{space 3} .0098649
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0845384{col 30}{space 2} .0571935{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.1966356{col 71}{space 3} .0275587
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0744664{col 30}{space 2} .0445802{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0129091{col 71}{space 3}  .161842
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1221092{col 30}{space 2} .0305281{col 41}{space 1}   -4.00{col 50}{space 3}0.000{col 58}{space 4}-.1819432{col 71}{space 3}-.0622752
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1435378{col 30}{space 2}  .029637{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .0854503{col 71}{space 3} .2016253
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1626178{col 30}{space 2} .0428687{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .0785966{col 71}{space 3} .2466389
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1405468{col 30}{space 2}  .197563{col 41}{space 1}   -0.71{col 50}{space 3}0.477{col 58}{space 4}-.5277631{col 71}{space 3} .2466695
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0493309{col 30}{space 2} .0692703{col 41}{space 1}   -0.71{col 50}{space 3}0.476{col 58}{space 4}-.1850981{col 71}{space 3} .0864363
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0450534{col 30}{space 2} .1295705{col 41}{space 1}   -0.35{col 50}{space 3}0.728{col 58}{space 4} -.299007{col 71}{space 3} .2089002
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0601968{col 30}{space 2} .0796832{col 41}{space 1}   -0.76{col 50}{space 3}0.450{col 58}{space 4}-.2163731{col 71}{space 3} .0959795
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2565331{col 30}{space 2} .0648188{col 41}{space 1}   -3.96{col 50}{space 3}0.000{col 58}{space 4}-.3835757{col 71}{space 3}-.1294905
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3120004{col 30}{space 2} .0231249{col 41}{space 1}   13.49{col 50}{space 3}0.000{col 58}{space 4} .2666765{col 71}{space 3} .3573243
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .716114{col 30}{space 2} .0414463{col 41}{space 1}   17.28{col 50}{space 3}0.000{col 58}{space 4} .6348807{col 71}{space 3} .7973473
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3571519{col 30}{space 2} .0346516{col 41}{space 1}   10.31{col 50}{space 3}0.000{col 58}{space 4}  .289236{col 71}{space 3} .4250679
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0090681{col 30}{space 2} .0873583{col 41}{space 1}   -0.10{col 50}{space 3}0.917{col 58}{space 4}-.1802872{col 71}{space 3} .1621511
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .52221912
         {txt}sigma_e {c |} {res} 1.1476523
             {txt}rho {c |} {res} .17153705{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,310
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,178

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1928                                         {txt}min = {res}         1
{txt}     between = {res}0.3304                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2861                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2375.55
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,178} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2295727{col 30}{space 2} .0269241{col 41}{space 1}    8.53{col 50}{space 3}0.000{col 58}{space 4} .1768024{col 71}{space 3}  .282343
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0012744{col 30}{space 2} .0044744{col 41}{space 1}    0.28{col 50}{space 3}0.776{col 58}{space 4}-.0074952{col 71}{space 3}  .010044
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0002189{col 30}{space 2}  .067682{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.1328731{col 71}{space 3} .1324354
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0017766{col 30}{space 2} .0009906{col 41}{space 1}   -1.79{col 50}{space 3}0.073{col 58}{space 4}-.0037181{col 71}{space 3} .0001649
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1623797{col 30}{space 2}  .035706{col 41}{space 1}   -4.55{col 50}{space 3}0.000{col 58}{space 4}-.2323621{col 71}{space 3}-.0923972
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .073537{col 30}{space 2} .0323488{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0101345{col 71}{space 3} .1369395
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0105612{col 30}{space 2} .0767355{col 41}{space 1}    0.14{col 50}{space 3}0.891{col 58}{space 4}-.1398375{col 71}{space 3}   .16096
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  -.12798{col 30}{space 2} .0493489{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.2247021{col 71}{space 3}-.0312579
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0285914{col 30}{space 2}  .084619{col 41}{space 1}    0.34{col 50}{space 3}0.735{col 58}{space 4}-.1372588{col 71}{space 3} .1944416
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .119952{col 30}{space 2} .0643809{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.0062323{col 71}{space 3} .2461362
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0116418{col 30}{space 2} .0468057{col 41}{space 1}   -0.25{col 50}{space 3}0.804{col 58}{space 4}-.1033794{col 71}{space 3} .0800958
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0061614{col 30}{space 2} .0295926{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-.0641618{col 71}{space 3}  .051839
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006886{col 30}{space 2}  .001104{col 41}{space 1}    0.62{col 50}{space 3}0.533{col 58}{space 4}-.0014751{col 71}{space 3} .0028524
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3636423{col 30}{space 2} .1476754{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0742039{col 71}{space 3} .6530807
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0431122{col 30}{space 2} .0898956{col 41}{space 1}   -0.48{col 50}{space 3}0.632{col 58}{space 4}-.2193042{col 71}{space 3} .1330799
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0533255{col 30}{space 2} .0604212{col 41}{space 1}   -0.88{col 50}{space 3}0.377{col 58}{space 4}-.1717488{col 71}{space 3} .0650978
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3652661{col 30}{space 2} .0988319{col 41}{space 1}   -3.70{col 50}{space 3}0.000{col 58}{space 4}-.5589731{col 71}{space 3}-.1715592
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2267675{col 30}{space 2} .0744527{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.3726922{col 71}{space 3}-.0808429
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0934347{col 30}{space 2} .0577277{col 41}{space 1}   -1.62{col 50}{space 3}0.106{col 58}{space 4}-.2065788{col 71}{space 3} .0197095
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2418129{col 30}{space 2} .0299353{col 41}{space 1}    8.08{col 50}{space 3}0.000{col 58}{space 4} .1831409{col 71}{space 3}  .300485
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .4041329{col 30}{space 2} .0250422{col 41}{space 1}   16.14{col 50}{space 3}0.000{col 58}{space 4} .3550511{col 71}{space 3} .4532147
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0052117{col 30}{space 2} .0723482{col 41}{space 1}   -0.07{col 50}{space 3}0.943{col 58}{space 4}-.1470115{col 71}{space 3}  .136588
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .25095518
         {txt}sigma_e {c |} {res} .86598892
             {txt}rho {c |} {res}  .0774724{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,811
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,302

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0735                                         {txt}min = {res}         1
{txt}     between = {res}0.1762                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1445                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1718.09
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,302} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1823227{col 30}{space 2} .0160136{col 41}{space 1}   11.39{col 50}{space 3}0.000{col 58}{space 4} .1509367{col 71}{space 3} .2137087
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0092072{col 30}{space 2} .0036714{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0020114{col 71}{space 3} .0164031
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0481527{col 30}{space 2} .0458849{col 41}{space 1}   -1.05{col 50}{space 3}0.294{col 58}{space 4}-.1380855{col 71}{space 3} .0417802
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0003133{col 30}{space 2} .0007575{col 41}{space 1}    0.41{col 50}{space 3}0.679{col 58}{space 4}-.0011713{col 71}{space 3} .0017979
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0813656{col 30}{space 2} .0335192{col 41}{space 1}   -2.43{col 50}{space 3}0.015{col 58}{space 4}-.1470621{col 71}{space 3}-.0156691
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0281915{col 30}{space 2} .0234059{col 41}{space 1}   -1.20{col 50}{space 3}0.228{col 58}{space 4}-.0740663{col 71}{space 3} .0176833
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0908121{col 30}{space 2} .0347677{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.1589555{col 71}{space 3}-.0226687
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0688465{col 30}{space 2} .0329042{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0043554{col 71}{space 3} .1333376
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0149795{col 30}{space 2} .0469126{col 41}{space 1}    0.32{col 50}{space 3}0.749{col 58}{space 4}-.0769675{col 71}{space 3} .1069264
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0595784{col 30}{space 2} .0516242{col 41}{space 1}    1.15{col 50}{space 3}0.248{col 58}{space 4}-.0416032{col 71}{space 3} .1607601
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0657703{col 30}{space 2} .0397327{col 41}{space 1}    1.66{col 50}{space 3}0.098{col 58}{space 4}-.0121044{col 71}{space 3}  .143645
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0803144{col 30}{space 2} .0380536{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0057307{col 71}{space 3} .1548982
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0136623{col 30}{space 2} .0072475{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0005426{col 71}{space 3} .0278672
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1174722{col 30}{space 2} .0453584{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0285713{col 71}{space 3} .2063731
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2390117{col 30}{space 2} .0459847{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .1488834{col 71}{space 3}   .32914
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0723879{col 30}{space 2} .0478458{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0213882{col 71}{space 3}  .166164
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2990915{col 30}{space 2} .0550551{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4}-.4069976{col 71}{space 3}-.1911854
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2653144{col 30}{space 2} .0640335{col 41}{space 1}   -4.14{col 50}{space 3}0.000{col 58}{space 4}-.3908176{col 71}{space 3}-.1398111
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2437739{col 30}{space 2} .0478099{col 41}{space 1}   -5.10{col 50}{space 3}0.000{col 58}{space 4}-.3374796{col 71}{space 3}-.1500681
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1538495{col 30}{space 2}  .019848{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .1149482{col 71}{space 3} .1927509
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6240478{col 30}{space 2} .0291795{col 41}{space 1}  -21.39{col 50}{space 3}0.000{col 58}{space 4}-.6812385{col 71}{space 3} -.566857
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.314512{col 30}{space 2} .0286699{col 41}{space 1}  -10.97{col 50}{space 3}0.000{col 58}{space 4}-.3707039{col 71}{space 3}  -.25832
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3545762{col 30}{space 2} .0291993{col 41}{space 1}  -12.14{col 50}{space 3}0.000{col 58}{space 4}-.4118058{col 71}{space 3}-.2973466
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.155433{col 30}{space 2} .0620822{col 41}{space 1}   18.61{col 50}{space 3}0.000{col 58}{space 4} 1.033755{col 71}{space 3} 1.277112
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .58590594
         {txt}sigma_e {c |} {res} .98203226
             {txt}rho {c |} {res}  .2625165{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,194
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0907                                         {txt}min = {res}         1
{txt}     between = {res}0.4418                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.3668                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  6404.59
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3044905{col 30}{space 2} .0145696{col 41}{space 1}   20.90{col 50}{space 3}0.000{col 58}{space 4} .2759345{col 71}{space 3} .3330464
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0296839{col 30}{space 2} .0050557{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .0197748{col 71}{space 3}  .039593
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0468902{col 30}{space 2}   .05635{col 41}{space 1}   -0.83{col 50}{space 3}0.405{col 58}{space 4}-.1573342{col 71}{space 3} .0635537
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022848{col 30}{space 2} .0009221{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.0040922{col 71}{space 3}-.0004775
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0870345{col 30}{space 2} .0325885{col 41}{space 1}   -2.67{col 50}{space 3}0.008{col 58}{space 4}-.1509068{col 71}{space 3}-.0231622
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .040881{col 30}{space 2} .0308258{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0195364{col 71}{space 3} .1012984
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1201718{col 30}{space 2} .0848682{col 41}{space 1}    1.42{col 50}{space 3}0.157{col 58}{space 4}-.0461669{col 71}{space 3} .2865106
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0528717{col 30}{space 2} .0443684{col 41}{space 1}   -1.19{col 50}{space 3}0.233{col 58}{space 4}-.1398321{col 71}{space 3} .0340888
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1808696{col 30}{space 2}  .065005{col 41}{space 1}   -2.78{col 50}{space 3}0.005{col 58}{space 4}-.3082771{col 71}{space 3}-.0534621
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0099211{col 30}{space 2} .0352765{col 41}{space 1}   -0.28{col 50}{space 3}0.779{col 58}{space 4}-.0790617{col 71}{space 3} .0592196
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0410044{col 30}{space 2} .0380104{col 41}{space 1}    1.08{col 50}{space 3}0.281{col 58}{space 4}-.0334946{col 71}{space 3} .1155033
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0813287{col 30}{space 2} .0302478{col 41}{space 1}   -2.69{col 50}{space 3}0.007{col 58}{space 4}-.1406132{col 71}{space 3}-.0220442
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0159333{col 30}{space 2} .0047083{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0067052{col 71}{space 3} .0251614
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2173914{col 30}{space 2} .0293896{col 41}{space 1}    7.40{col 50}{space 3}0.000{col 58}{space 4} .1597888{col 71}{space 3}  .274994
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0108183{col 30}{space 2} .1062257{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.2190169{col 71}{space 3} .1973803
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1024774{col 30}{space 2} .0575393{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.2152524{col 71}{space 3} .0102976
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0405005{col 30}{space 2}  .078007{col 41}{space 1}   -0.52{col 50}{space 3}0.604{col 58}{space 4}-.1933915{col 71}{space 3} .1123904
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2641479{col 30}{space 2} .0485362{col 41}{space 1}   -5.44{col 50}{space 3}0.000{col 58}{space 4}-.3592771{col 71}{space 3}-.1690187
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3506642{col 30}{space 2} .0507076{col 41}{space 1}   -6.92{col 50}{space 3}0.000{col 58}{space 4}-.4500491{col 71}{space 3}-.2512792
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2566813{col 30}{space 2} .0174491{col 41}{space 1}   14.71{col 50}{space 3}0.000{col 58}{space 4} .2224818{col 71}{space 3} .2908808
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0558696{col 30}{space 2} .0333548{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0095045{col 71}{space 3} .1212438
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0347573{col 30}{space 2} .0275757{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.0192901{col 71}{space 3} .0888047
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0077076{col 30}{space 2} .0325481{col 41}{space 1}    0.24{col 50}{space 3}0.813{col 58}{space 4}-.0560854{col 71}{space 3} .0715006
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5046731{col 30}{space 2} .0726581{col 41}{space 1}    6.95{col 50}{space 3}0.000{col 58}{space 4} .3622659{col 71}{space 3} .6470803
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .61243205
         {txt}sigma_e {c |} {res} 1.1356969
             {txt}rho {c |} {res} .22528526{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,749
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,278

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0533                                         {txt}min = {res}         1
{txt}     between = {res}0.4476                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.2736                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4752.94
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,278} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1873559{col 30}{space 2} .0118875{col 41}{space 1}   15.76{col 50}{space 3}0.000{col 58}{space 4} .1640568{col 71}{space 3}  .210655
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0343303{col 30}{space 2} .0050944{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .0243455{col 71}{space 3} .0443151
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0360607{col 30}{space 2} .0545738{col 41}{space 1}   -0.66{col 50}{space 3}0.509{col 58}{space 4}-.1430233{col 71}{space 3} .0709019
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0022837{col 30}{space 2} .0009121{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0004961{col 71}{space 3} .0040713
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0102122{col 30}{space 2} .0305644{col 41}{space 1}   -0.33{col 50}{space 3}0.738{col 58}{space 4}-.0701174{col 71}{space 3} .0496929
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1844893{col 30}{space 2} .0302425{col 41}{space 1}    6.10{col 50}{space 3}0.000{col 58}{space 4} .1252151{col 71}{space 3} .2437634
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0184099{col 30}{space 2} .0566123{col 41}{space 1}    0.33{col 50}{space 3}0.745{col 58}{space 4}-.0925482{col 71}{space 3}  .129368
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1063393{col 30}{space 2} .0340054{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0396899{col 71}{space 3} .1729887
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0965136{col 30}{space 2}   .03476{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0283853{col 71}{space 3} .1646419
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1470882{col 30}{space 2} .0278331{col 41}{space 1}   -5.28{col 50}{space 3}0.000{col 58}{space 4}-.2016401{col 71}{space 3}-.0925363
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0015922{col 30}{space 2} .0313863{col 41}{space 1}    0.05{col 50}{space 3}0.960{col 58}{space 4}-.0599237{col 71}{space 3} .0631082
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.04062{col 30}{space 2} .0234543{col 41}{space 1}   -1.73{col 50}{space 3}0.083{col 58}{space 4}-.0865895{col 71}{space 3} .0053495
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0039889{col 30}{space 2} .0019941{col 41}{space 1}    2.00{col 50}{space 3}0.045{col 58}{space 4} .0000805{col 71}{space 3} .0078974
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1940033{col 30}{space 2} .0253036{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .1444091{col 71}{space 3} .2435975
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0082455{col 30}{space 2} .0831099{col 41}{space 1}    0.10{col 50}{space 3}0.921{col 58}{space 4}-.1546468{col 71}{space 3} .1711379
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0135484{col 30}{space 2}  .056965{col 41}{space 1}    0.24{col 50}{space 3}0.812{col 58}{space 4} -.098101{col 71}{space 3} .1251977
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0491072{col 30}{space 2} .0644305{col 41}{space 1}   -0.76{col 50}{space 3}0.446{col 58}{space 4}-.1753887{col 71}{space 3} .0771743
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2401616{col 30}{space 2} .0500014{col 41}{space 1}   -4.80{col 50}{space 3}0.000{col 58}{space 4}-.3381626{col 71}{space 3}-.1421605
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3914626{col 30}{space 2} .0504228{col 41}{space 1}   -7.76{col 50}{space 3}0.000{col 58}{space 4}-.4902894{col 71}{space 3}-.2926357
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .5218396{col 30}{space 2} .0193699{col 41}{space 1}   26.94{col 50}{space 3}0.000{col 58}{space 4} .4838753{col 71}{space 3} .5598039
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.107975{col 30}{space 2} .0331317{col 41}{space 1}   -3.26{col 50}{space 3}0.001{col 58}{space 4} -.172912{col 71}{space 3} -.043038
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .1279933{col 30}{space 2} .0333449{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0626384{col 71}{space 3} .1933482
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4340833{col 30}{space 2} .0318709{col 41}{space 1}   13.62{col 50}{space 3}0.000{col 58}{space 4} .3716174{col 71}{space 3} .4965491
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2449058{col 30}{space 2} .0312122{col 41}{space 1}    7.85{col 50}{space 3}0.000{col 58}{space 4} .1837311{col 71}{space 3} .3060805
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3507811{col 30}{space 2}    .0305{col 41}{space 1}   11.50{col 50}{space 3}0.000{col 58}{space 4} .2910023{col 71}{space 3} .4105599
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.0863464{col 30}{space 2} .0813296{col 41}{space 1}   -1.06{col 50}{space 3}0.288{col 58}{space 4}-.2457494{col 71}{space 3} .0730567
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .62690062
         {txt}sigma_e {c |} {res} 1.2252119
             {txt}rho {c |} {res} .20748339{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S13_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S13_farmer.rtf not found)
(output written to {browse  `"S13_farmer.rtf"'})

{com}. 
. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    62,289
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    26,569

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0292                                         {txt}min = {res}         1
{txt}     between = {res}0.4316                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.3399                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 25922.83
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:26,569} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0251036{col 30}{space 2} .0073155{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .0107654{col 71}{space 3} .0394418
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0135794{col 30}{space 2} .0030674{col 41}{space 1}   -4.43{col 50}{space 3}0.000{col 58}{space 4}-.0195914{col 71}{space 3}-.0075675
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0942188{col 30}{space 2} .0338063{col 41}{space 1}   -2.79{col 50}{space 3}0.005{col 58}{space 4}-.1604779{col 71}{space 3}-.0279597
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0030504{col 30}{space 2}  .000574{col 41}{space 1}   -5.31{col 50}{space 3}0.000{col 58}{space 4}-.0041754{col 71}{space 3}-.0019254
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0337457{col 30}{space 2} .0209697{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0073541{col 71}{space 3} .0748454
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .289167{col 30}{space 2} .0172447{col 41}{space 1}   16.77{col 50}{space 3}0.000{col 58}{space 4}  .255368{col 71}{space 3}  .322966
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1026402{col 30}{space 2}  .034518{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4} .0349861{col 71}{space 3} .1702943
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .238757{col 30}{space 2}  .021833{col 41}{space 1}   10.94{col 50}{space 3}0.000{col 58}{space 4} .1959652{col 71}{space 3} .2815488
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2838046{col 30}{space 2} .0279496{col 41}{space 1}   10.15{col 50}{space 3}0.000{col 58}{space 4} .2290244{col 71}{space 3} .3385848
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2175232{col 30}{space 2} .0224457{col 41}{space 1}    9.69{col 50}{space 3}0.000{col 58}{space 4} .1735304{col 71}{space 3}  .261516
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2623183{col 30}{space 2} .0211545{col 41}{space 1}   12.40{col 50}{space 3}0.000{col 58}{space 4} .2208561{col 71}{space 3} .3037804
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0302981{col 30}{space 2} .0161433{col 41}{space 1}   -1.88{col 50}{space 3}0.061{col 58}{space 4}-.0619385{col 71}{space 3} .0013423
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0013336{col 30}{space 2} .0012464{col 41}{space 1}   -1.07{col 50}{space 3}0.285{col 58}{space 4}-.0037765{col 71}{space 3} .0011093
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.031865{col 30}{space 2} .0184896{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4} -.068104{col 71}{space 3}  .004374
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0553847{col 30}{space 2} .0473557{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0374307{col 71}{space 3} .1482002
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6308652{col 30}{space 2} .0323554{col 41}{space 1}   19.50{col 50}{space 3}0.000{col 58}{space 4} .5674497{col 71}{space 3} .6942807
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8197511{col 30}{space 2} .0382476{col 41}{space 1}   21.43{col 50}{space 3}0.000{col 58}{space 4} .7447872{col 71}{space 3} .8947149
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3771258{col 30}{space 2} .0351382{col 41}{space 1}   10.73{col 50}{space 3}0.000{col 58}{space 4} .3082561{col 71}{space 3} .4459954
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5301054{col 30}{space 2} .0304251{col 41}{space 1}   17.42{col 50}{space 3}0.000{col 58}{space 4} .4704734{col 71}{space 3} .5897375
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1932032{col 30}{space 2} .0103967{col 41}{space 1}  -18.58{col 50}{space 3}0.000{col 58}{space 4}-.2135804{col 71}{space 3}-.1728259
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.810744{col 30}{space 2} .0397648{col 41}{space 1}  -20.39{col 50}{space 3}0.000{col 58}{space 4}-.8886816{col 71}{space 3}-.7328064
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-2.107373{col 30}{space 2}  .040038{col 41}{space 1}  -52.63{col 50}{space 3}0.000{col 58}{space 4}-2.185846{col 71}{space 3}  -2.0289
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.581303{col 30}{space 2} .0405851{col 41}{space 1}  -38.96{col 50}{space 3}0.000{col 58}{space 4}-1.660849{col 71}{space 3}-1.501758
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-1.137962{col 30}{space 2} .0400666{col 41}{space 1}  -28.40{col 50}{space 3}0.000{col 58}{space 4}-1.216491{col 71}{space 3}-1.059433
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}-.4273384{col 30}{space 2} .0475009{col 41}{space 1}   -9.00{col 50}{space 3}0.000{col 58}{space 4}-.5204384{col 71}{space 3}-.3342384
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1302052{col 30}{space 2} .0480993{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4}-.2244781{col 71}{space 3}-.0359323
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0503172{col 30}{space 2} .0353418{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4}-.0189515{col 71}{space 3} .1195859
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0499818{col 30}{space 2} .0414761{col 41}{space 1}   -1.21{col 50}{space 3}0.228{col 58}{space 4}-.1312735{col 71}{space 3} .0313099
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0002358{col 30}{space 2} .0360924{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.0709756{col 71}{space 3} .0705039
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1630644{col 30}{space 2} .0418184{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0811018{col 71}{space 3}  .245027
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.030966{col 30}{space 2} .0430599{col 41}{space 1}   -0.72{col 50}{space 3}0.472{col 58}{space 4}-.1153618{col 71}{space 3} .0534298
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2490479{col 30}{space 2} .0402724{col 41}{space 1}    6.18{col 50}{space 3}0.000{col 58}{space 4} .1701154{col 71}{space 3} .3279803
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .2151668{col 30}{space 2} .0556041{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .1061848{col 71}{space 3} .3241488
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3037904{col 30}{space 2} .0428774{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .2197523{col 71}{space 3} .3878284
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .2737937{col 30}{space 2} .0432646{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .1889966{col 71}{space 3} .3585908
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.442279{col 30}{space 2} .0617027{col 41}{space 1}   71.99{col 50}{space 3}0.000{col 58}{space 4} 4.321344{col 71}{space 3} 4.563214
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0101946
         {txt}sigma_e {c |} {res} 1.3813753
             {txt}rho {c |} {res} .34844686{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,874
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,641

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0325                                         {txt}min = {res}         1
{txt}     between = {res}0.3885                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.2918                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2311.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,641} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0311827{col 30}{space 2} .0140754{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0035953{col 71}{space 3}   .05877
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0058082{col 30}{space 2} .0090848{col 41}{space 1}    0.64{col 50}{space 3}0.523{col 58}{space 4}-.0119977{col 71}{space 3}  .023614
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0376187{col 30}{space 2} .0756952{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.1107411{col 71}{space 3} .1859784
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0045169{col 30}{space 2} .0012572{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4} -.006981{col 71}{space 3}-.0020529
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0583438{col 30}{space 2} .0460888{col 41}{space 1}    1.27{col 50}{space 3}0.206{col 58}{space 4}-.0319885{col 71}{space 3} .1486761
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .249893{col 30}{space 2} .0389069{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4} .1736368{col 71}{space 3} .3261491
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1070066{col 30}{space 2} .1977079{col 41}{space 1}    0.54{col 50}{space 3}0.588{col 58}{space 4}-.2804938{col 71}{space 3} .4945069
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1989103{col 30}{space 2} .0474207{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1059675{col 71}{space 3} .2918532
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4422835{col 30}{space 2} .0575837{col 41}{space 1}    7.68{col 50}{space 3}0.000{col 58}{space 4} .3294215{col 71}{space 3} .5551456
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1260662{col 30}{space 2}  .088575{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4}-.0475376{col 71}{space 3} .2996701
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2085056{col 30}{space 2} .0673129{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .0765747{col 71}{space 3} .3404364
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1039221{col 30}{space 2} .0360547{col 41}{space 1}   -2.88{col 50}{space 3}0.004{col 58}{space 4}-.1745881{col 71}{space 3}-.0332562
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0094769{col 30}{space 2}  .005636{col 41}{space 1}   -1.68{col 50}{space 3}0.093{col 58}{space 4}-.0205233{col 71}{space 3} .0015695
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .237421{col 30}{space 2} .0371968{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .1645167{col 71}{space 3} .3103253
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .212924{col 30}{space 2} .3164221{col 41}{space 1}    0.67{col 50}{space 3}0.501{col 58}{space 4} -.407252{col 71}{space 3} .8330999
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5485407{col 30}{space 2} .0712755{col 41}{space 1}    7.70{col 50}{space 3}0.000{col 58}{space 4} .4088433{col 71}{space 3}  .688238
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6207466{col 30}{space 2} .0845725{col 41}{space 1}    7.34{col 50}{space 3}0.000{col 58}{space 4} .4549875{col 71}{space 3} .7865057
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6926626{col 30}{space 2} .1345106{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4} .4290267{col 71}{space 3} .9562985
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5426591{col 30}{space 2} .0838892{col 41}{space 1}    6.47{col 50}{space 3}0.000{col 58}{space 4} .3782393{col 71}{space 3} .7070789
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1105562{col 30}{space 2} .0196382{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.1490463{col 71}{space 3}-.0720661
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1914492{col 30}{space 2} .0274387{col 41}{space 1}   -6.98{col 50}{space 3}0.000{col 58}{space 4}-.2452281{col 71}{space 3}-.1376702
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.077491{col 30}{space 2} .0989728{col 41}{space 1}   20.99{col 50}{space 3}0.000{col 58}{space 4} 1.883508{col 71}{space 3} 2.271474
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86581815
         {txt}sigma_e {c |} {res} 1.0681939
             {txt}rho {c |} {res}   .396493{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,351
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0464                                         {txt}min = {res}         1
{txt}     between = {res}0.4496                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.3554                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3276.71
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0016637{col 30}{space 2} .0194415{col 41}{space 1}    0.09{col 50}{space 3}0.932{col 58}{space 4} -.036441{col 71}{space 3} .0397684
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0098839{col 30}{space 2} .0111368{col 41}{space 1}    0.89{col 50}{space 3}0.375{col 58}{space 4}-.0119437{col 71}{space 3} .0317116
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3604768{col 30}{space 2} .0976779{col 41}{space 1}   -3.69{col 50}{space 3}0.000{col 58}{space 4} -.551922{col 71}{space 3}-.1690316
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0086606{col 30}{space 2} .0017105{col 41}{space 1}   -5.06{col 50}{space 3}0.000{col 58}{space 4}-.0120131{col 71}{space 3}-.0053082
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1084976{col 30}{space 2} .0574474{col 41}{space 1}   -1.89{col 50}{space 3}0.059{col 58}{space 4}-.2210923{col 71}{space 3} .0040972
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2672491{col 30}{space 2} .0546111{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .1602134{col 71}{space 3} .3742849
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3690265{col 30}{space 2} .1639352{col 41}{space 1}    2.25{col 50}{space 3}0.024{col 58}{space 4} .0477195{col 71}{space 3} .6903336
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4122345{col 30}{space 2} .0653418{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4}  .284167{col 71}{space 3} .5403021
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6070093{col 30}{space 2} .1373145{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .3378779{col 71}{space 3} .8761407
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2760721{col 30}{space 2} .0755847{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .1279288{col 71}{space 3} .4242154
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3693812{col 30}{space 2} .0562486{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .2591359{col 71}{space 3} .4796265
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0934767{col 30}{space 2} .0414563{col 41}{space 1}   -2.25{col 50}{space 3}0.024{col 58}{space 4}-.1747296{col 71}{space 3}-.0122238
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0048512{col 30}{space 2} .0301498{col 41}{space 1}   -0.16{col 50}{space 3}0.872{col 58}{space 4}-.0639439{col 71}{space 3} .0542414
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.007603{col 30}{space 2} .0575172{col 41}{space 1}   -0.13{col 50}{space 3}0.895{col 58}{space 4}-.1203346{col 71}{space 3} .1051287
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1544311{col 30}{space 2} .2539098{col 41}{space 1}    0.61{col 50}{space 3}0.543{col 58}{space 4} -.343223{col 71}{space 3} .6520852
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5940462{col 30}{space 2} .1006993{col 41}{space 1}    5.90{col 50}{space 3}0.000{col 58}{space 4} .3966791{col 71}{space 3} .7914132
{txt}electricity_mean {c |}{col 18}{res}{space 2}  1.00662{col 30}{space 2} .1731482{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .6672561{col 71}{space 3} 1.345985
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6625895{col 30}{space 2} .1107414{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .4455404{col 71}{space 3} .8796385
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7265061{col 30}{space 2} .0926004{col 41}{space 1}    7.85{col 50}{space 3}0.000{col 58}{space 4} .5450127{col 71}{space 3} .9079994
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.199166{col 30}{space 2} .0323928{col 41}{space 1}   -6.15{col 50}{space 3}0.000{col 58}{space 4}-.2626547{col 71}{space 3}-.1356774
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2899742{col 30}{space 2} .0555268{col 41}{space 1}   -5.22{col 50}{space 3}0.000{col 58}{space 4}-.3988047{col 71}{space 3}-.1811437
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0246663{col 30}{space 2} .0459424{col 41}{space 1}   -0.54{col 50}{space 3}0.591{col 58}{space 4}-.1147117{col 71}{space 3} .0653791
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  4.34664{col 30}{space 2} .1311937{col 41}{space 1}   33.13{col 50}{space 3}0.000{col 58}{space 4} 4.089505{col 71}{space 3} 4.603775
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .98729316
         {txt}sigma_e {c |} {res} 1.5005496
             {txt}rho {c |} {res} .30211651{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,310
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,178

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0282                                         {txt}min = {res}         1
{txt}     between = {res}0.2284                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1636                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1249.83
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,178} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2642321{col 30}{space 2} .0438652{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4}  .178258{col 71}{space 3} .3502062
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0089937{col 30}{space 2} .0082617{col 41}{space 1}    1.09{col 50}{space 3}0.276{col 58}{space 4}-.0071989{col 71}{space 3} .0251863
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0951705{col 30}{space 2}  .130235{col 41}{space 1}   -0.73{col 50}{space 3}0.465{col 58}{space 4}-.3504263{col 71}{space 3} .1600853
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .002277{col 30}{space 2} .0018123{col 41}{space 1}    1.26{col 50}{space 3}0.209{col 58}{space 4}-.0012751{col 71}{space 3} .0058292
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0763914{col 30}{space 2}  .077969{col 41}{space 1}    0.98{col 50}{space 3}0.327{col 58}{space 4}-.0764251{col 71}{space 3} .2292078
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3086843{col 30}{space 2} .0572855{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .1964067{col 71}{space 3} .4209618
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3286214{col 30}{space 2} .1498803{col 41}{space 1}    2.19{col 50}{space 3}0.028{col 58}{space 4} .0348613{col 71}{space 3} .6223815
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1102566{col 30}{space 2} .0949774{col 41}{space 1}    1.16{col 50}{space 3}0.246{col 58}{space 4}-.0758956{col 71}{space 3} .2964089
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1884514{col 30}{space 2} .1862645{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.1766203{col 71}{space 3} .5535232
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .3413941{col 30}{space 2} .1165613{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .1129381{col 71}{space 3} .5698501
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2339856{col 30}{space 2} .0844402{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4}-.3994853{col 71}{space 3} -.068486
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1520573{col 30}{space 2} .0513865{col 41}{space 1}   -2.96{col 50}{space 3}0.003{col 58}{space 4}-.2527729{col 71}{space 3}-.0513417
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0007852{col 30}{space 2} .0016566{col 41}{space 1}   -0.47{col 50}{space 3}0.636{col 58}{space 4}-.0040322{col 71}{space 3} .0024617
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1357529{col 30}{space 2} .2453226{col 41}{space 1}    0.55{col 50}{space 3}0.580{col 58}{space 4}-.3450706{col 71}{space 3} .6165765
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1338757{col 30}{space 2} .1820848{col 41}{space 1}    0.74{col 50}{space 3}0.462{col 58}{space 4}-.2230039{col 71}{space 3} .4907553
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4407138{col 30}{space 2}  .115586{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .2141693{col 71}{space 3} .6672582
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9050659{col 30}{space 2} .2050121{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .5032495{col 71}{space 3} 1.306882
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1664721{col 30}{space 2} .1483487{col 41}{space 1}    1.12{col 50}{space 3}0.262{col 58}{space 4}-.1242861{col 71}{space 3} .4572303
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6704133{col 30}{space 2} .1037567{col 41}{space 1}    6.46{col 50}{space 3}0.000{col 58}{space 4} .4670539{col 71}{space 3} .8737726
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2549805{col 30}{space 2} .0523996{col 41}{space 1}   -4.87{col 50}{space 3}0.000{col 58}{space 4}-.3576819{col 71}{space 3}-.1522791
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0016887{col 30}{space 2} .0482116{col 41}{space 1}    0.04{col 50}{space 3}0.972{col 58}{space 4}-.0928042{col 71}{space 3} .0961816
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.943075{col 30}{space 2} .1392253{col 41}{space 1}   28.32{col 50}{space 3}0.000{col 58}{space 4} 3.670199{col 71}{space 3} 4.215952
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63799783
         {txt}sigma_e {c |} {res} 1.5882674
             {txt}rho {c |} {res} .13893925{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,811
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,302

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0208                                         {txt}min = {res}         1
{txt}     between = {res}0.3044                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2583                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3457.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,302} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0358132{col 30}{space 2} .0201719{col 41}{space 1}    1.78{col 50}{space 3}0.076{col 58}{space 4}-.0037231{col 71}{space 3} .0753495
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0226739{col 30}{space 2} .0055557{col 41}{space 1}   -4.08{col 50}{space 3}0.000{col 58}{space 4}-.0335628{col 71}{space 3}-.0117851
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .166546{col 30}{space 2} .0665516{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0361072{col 71}{space 3} .2969847
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0031988{col 30}{space 2} .0011743{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0008973{col 71}{space 3} .0055004
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3210909{col 30}{space 2} .0503761{col 41}{space 1}    6.37{col 50}{space 3}0.000{col 58}{space 4} .2223555{col 71}{space 3} .4198263
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2689716{col 30}{space 2} .0336622{col 41}{space 1}    7.99{col 50}{space 3}0.000{col 58}{space 4} .2029948{col 71}{space 3} .3349484
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0002655{col 30}{space 2} .0497762{col 41}{space 1}    0.01{col 50}{space 3}0.996{col 58}{space 4} -.097294{col 71}{space 3}  .097825
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1524148{col 30}{space 2} .0477446{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0588371{col 71}{space 3} .2459925
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1148817{col 30}{space 2} .0625085{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0076327{col 71}{space 3}  .237396
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .203391{col 30}{space 2} .0748537{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0566804{col 71}{space 3} .3501016
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3487736{col 30}{space 2} .0534348{col 41}{space 1}    6.53{col 50}{space 3}0.000{col 58}{space 4} .2440434{col 71}{space 3} .4535038
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0342213{col 30}{space 2} .0554071{col 41}{space 1}   -0.62{col 50}{space 3}0.537{col 58}{space 4}-.1428171{col 71}{space 3} .0743746
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0161008{col 30}{space 2} .0108939{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.0374525{col 71}{space 3} .0052508
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2313281{col 30}{space 2} .0665531{col 41}{space 1}    3.48{col 50}{space 3}0.001{col 58}{space 4} .1008865{col 71}{space 3} .3617697
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0491491{col 30}{space 2} .0667671{col 41}{space 1}    0.74{col 50}{space 3}0.462{col 58}{space 4} -.081712{col 71}{space 3} .1800103
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .725461{col 30}{space 2} .0700078{col 41}{space 1}   10.36{col 50}{space 3}0.000{col 58}{space 4} .5882483{col 71}{space 3} .8626738
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.056574{col 30}{space 2} .0757597{col 41}{space 1}   13.95{col 50}{space 3}0.000{col 58}{space 4} .9080877{col 71}{space 3}  1.20506
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3024437{col 30}{space 2} .0947971{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .1166449{col 71}{space 3} .4882425
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1322748{col 30}{space 2} .0673255{col 41}{space 1}    1.96{col 50}{space 3}0.049{col 58}{space 4} .0003192{col 71}{space 3} .2642303
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1296171{col 30}{space 2}  .027553{col 41}{space 1}   -4.70{col 50}{space 3}0.000{col 58}{space 4}  -.18362{col 71}{space 3}-.0756142
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1537294{col 30}{space 2} .0414168{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.2349048{col 71}{space 3} -.072554
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.3205604{col 30}{space 2} .0408481{col 41}{space 1}   -7.85{col 50}{space 3}0.000{col 58}{space 4}-.4006211{col 71}{space 3}-.2404996
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0245244{col 30}{space 2} .0409694{col 41}{space 1}   -0.60{col 50}{space 3}0.549{col 58}{space 4}-.1048229{col 71}{space 3}  .055774
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  3.49896{col 30}{space 2} .0961199{col 41}{space 1}   36.40{col 50}{space 3}0.000{col 58}{space 4} 3.310569{col 71}{space 3} 3.687351
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .95107599
         {txt}sigma_e {c |} {res} 1.3782081
             {txt}rho {c |} {res} .32259078{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,194
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0189                                         {txt}min = {res}         1
{txt}     between = {res}0.3631                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.3137                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4406.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0189262{col 30}{space 2} .0166337{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0136751{col 71}{space 3} .0515276
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.022934{col 30}{space 2}  .006872{col 41}{space 1}   -3.34{col 50}{space 3}0.001{col 58}{space 4} -.036403{col 71}{space 3} -.009465
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2179885{col 30}{space 2}  .080676{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4}-.3761106{col 71}{space 3}-.0598665
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028608{col 30}{space 2} .0013242{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.0054561{col 71}{space 3}-.0002655
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0440088{col 30}{space 2} .0455002{col 41}{space 1}    0.97{col 50}{space 3}0.333{col 58}{space 4}  -.04517{col 71}{space 3} .1331876
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4030258{col 30}{space 2} .0419502{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4} .3208049{col 71}{space 3} .4852468
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0117965{col 30}{space 2} .0975869{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-.2030633{col 71}{space 3} .1794703
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3905528{col 30}{space 2} .0515681{col 41}{space 1}    7.57{col 50}{space 3}0.000{col 58}{space 4} .2894812{col 71}{space 3} .4916243
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1323229{col 30}{space 2} .0727755{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0103144{col 71}{space 3} .2749602
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2150661{col 30}{space 2} .0421415{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .1324701{col 71}{space 3}  .297662
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .282056{col 30}{space 2} .0463153{col 41}{space 1}    6.09{col 50}{space 3}0.000{col 58}{space 4} .1912797{col 71}{space 3} .3728323
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0597786{col 30}{space 2} .0387728{col 41}{space 1}   -1.54{col 50}{space 3}0.123{col 58}{space 4} -.135772{col 71}{space 3} .0162147
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0057816{col 30}{space 2} .0040952{col 41}{space 1}   -1.41{col 50}{space 3}0.158{col 58}{space 4} -.013808{col 71}{space 3} .0022448
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1149116{col 30}{space 2} .0365849{col 41}{space 1}   -3.14{col 50}{space 3}0.002{col 58}{space 4}-.1866167{col 71}{space 3}-.0432064
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .6865511{col 30}{space 2} .1318106{col 41}{space 1}    5.21{col 50}{space 3}0.000{col 58}{space 4} .4282071{col 71}{space 3} .9448951
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .679308{col 30}{space 2} .0731069{col 41}{space 1}    9.29{col 50}{space 3}0.000{col 58}{space 4}  .536021{col 71}{space 3} .8225949
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8594142{col 30}{space 2} .0958895{col 41}{space 1}    8.96{col 50}{space 3}0.000{col 58}{space 4} .6714741{col 71}{space 3} 1.047354
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .203068{col 30}{space 2} .0632713{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0790585{col 71}{space 3} .3270775
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6148352{col 30}{space 2} .0665127{col 41}{space 1}    9.24{col 50}{space 3}0.000{col 58}{space 4} .4844726{col 71}{space 3} .7451977
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2863429{col 30}{space 2}    .0216{col 41}{space 1}  -13.26{col 50}{space 3}0.000{col 58}{space 4}-.3286782{col 71}{space 3}-.2440075
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0515798{col 30}{space 2}  .038645{col 41}{space 1}   -1.33{col 50}{space 3}0.182{col 58}{space 4}-.1273226{col 71}{space 3} .0241629
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0419616{col 30}{space 2} .0328809{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.1064069{col 71}{space 3} .0224838
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1164724{col 30}{space 2} .0428583{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-.2004731{col 71}{space 3}-.0324717
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.690833{col 30}{space 2} .1034217{col 41}{space 1}   35.69{col 50}{space 3}0.000{col 58}{space 4}  3.48813{col 71}{space 3} 3.893536
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.1536625
         {txt}sigma_e {c |} {res} 1.3111645
             {txt}rho {c |} {res} .43636005{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,749
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,278

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0381                                         {txt}min = {res}         1
{txt}     between = {res}0.3225                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1938                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2388.31
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,278} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0186411{col 30}{space 2}  .013688{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0081869{col 71}{space 3}  .045469
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.005199{col 30}{space 2} .0065596{col 41}{space 1}   -0.79{col 50}{space 3}0.428{col 58}{space 4}-.0180555{col 71}{space 3} .0076576
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0774025{col 30}{space 2} .0688519{col 41}{space 1}   -1.12{col 50}{space 3}0.261{col 58}{space 4}-.2123497{col 71}{space 3} .0575447
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.004922{col 30}{space 2} .0012752{col 41}{space 1}   -3.86{col 50}{space 3}0.000{col 58}{space 4}-.0074213{col 71}{space 3}-.0024228
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0558891{col 30}{space 2} .0412947{col 41}{space 1}    1.35{col 50}{space 3}0.176{col 58}{space 4}-.0250469{col 71}{space 3} .1368252
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2670169{col 30}{space 2} .0368506{col 41}{space 1}    7.25{col 50}{space 3}0.000{col 58}{space 4}  .194791{col 71}{space 3} .3392428
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2514001{col 30}{space 2} .0640308{col 41}{space 1}    3.93{col 50}{space 3}0.000{col 58}{space 4}  .125902{col 71}{space 3} .3768981
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2777507{col 30}{space 2} .0394091{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .2005103{col 71}{space 3} .3549912
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .470074{col 30}{space 2}  .042211{col 41}{space 1}   11.14{col 50}{space 3}0.000{col 58}{space 4}  .387342{col 71}{space 3}  .552806
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1795151{col 30}{space 2} .0332671{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .1143128{col 71}{space 3} .2447175
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2510568{col 30}{space 2} .0356096{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .1812632{col 71}{space 3} .3208503
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0492934{col 30}{space 2} .0275053{col 41}{space 1}    1.79{col 50}{space 3}0.073{col 58}{space 4} -.004616{col 71}{space 3} .1032027
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0008308{col 30}{space 2} .0018384{col 41}{space 1}    0.45{col 50}{space 3}0.651{col 58}{space 4}-.0027724{col 71}{space 3} .0044341
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1249074{col 30}{space 2} .0323155{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.1882445{col 71}{space 3}-.0615702
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .139881{col 30}{space 2} .1077165{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.0712396{col 71}{space 3} .3510015
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4494568{col 30}{space 2} .0728253{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .3067218{col 71}{space 3} .5921917
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3268847{col 30}{space 2} .0856236{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .1590655{col 71}{space 3} .4947039
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5036094{col 30}{space 2} .0684517{col 41}{space 1}    7.36{col 50}{space 3}0.000{col 58}{space 4} .3694465{col 71}{space 3} .6377723
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7771963{col 30}{space 2} .0661322{col 41}{space 1}   11.75{col 50}{space 3}0.000{col 58}{space 4} .6475796{col 71}{space 3}  .906813
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1995361{col 30}{space 2} .0253328{col 41}{space 1}   -7.88{col 50}{space 3}0.000{col 58}{space 4}-.2491874{col 71}{space 3}-.1498847
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1801244{col 30}{space 2} .0381909{col 41}{space 1}   -4.72{col 50}{space 3}0.000{col 58}{space 4}-.2549773{col 71}{space 3}-.1052716
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1871885{col 30}{space 2} .0383626{col 41}{space 1}   -4.88{col 50}{space 3}0.000{col 58}{space 4}-.2623779{col 71}{space 3}-.1119991
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1949543{col 30}{space 2} .0381189{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4} .1202427{col 71}{space 3} .2696659
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0379776{col 30}{space 2} .0379304{col 41}{space 1}    1.00{col 50}{space 3}0.317{col 58}{space 4}-.0363647{col 71}{space 3} .1123199
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .1771123{col 30}{space 2} .0354934{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .1075466{col 71}{space 3} .2466781
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.070836{col 30}{space 2}  .113665{col 41}{space 1}   27.02{col 50}{space 3}0.000{col 58}{space 4} 2.848057{col 71}{space 3} 3.293616
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0308654
         {txt}sigma_e {c |} {res} 1.4216742
             {txt}rho {c |} {res} .34459737{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S14_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S14_farmer.rtf not found)
(output written to {browse  `"S14_farmer.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                  S15_S18                                     *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(10,046 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0317                                         {txt}min = {res}         1
{txt}     between = {res}0.3605                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2782                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 17580.32
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1189621{col 30}{space 2} .0065459{col 41}{space 1}   18.17{col 50}{space 3}0.000{col 58}{space 4} .1061324{col 71}{space 3} .1317919
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0122976{col 30}{space 2} .0025939{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4}-.0173817{col 71}{space 3}-.0072136
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0239236{col 30}{space 2} .0297622{col 41}{space 1}    0.80{col 50}{space 3}0.421{col 58}{space 4}-.0344092{col 71}{space 3} .0822564
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0006713{col 30}{space 2} .0004923{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0002937{col 71}{space 3} .0016362
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0600559{col 30}{space 2} .0181261{col 41}{space 1}    3.31{col 50}{space 3}0.001{col 58}{space 4} .0245293{col 71}{space 3} .0955825
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2888388{col 30}{space 2} .0154448{col 41}{space 1}   18.70{col 50}{space 3}0.000{col 58}{space 4} .2585675{col 71}{space 3} .3191101
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1029198{col 30}{space 2} .0317219{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0407459{col 71}{space 3} .1650937
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1621579{col 30}{space 2} .0200118{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .1229355{col 71}{space 3} .2013803
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1515415{col 30}{space 2} .0243247{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4}  .103866{col 71}{space 3} .1992171
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1322495{col 30}{space 2} .0210269{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .0910375{col 71}{space 3} .1734615
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1963682{col 30}{space 2} .0192067{col 41}{space 1}   10.22{col 50}{space 3}0.000{col 58}{space 4} .1587238{col 71}{space 3} .2340125
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0585904{col 30}{space 2} .0145607{col 41}{space 1}   -4.02{col 50}{space 3}0.000{col 58}{space 4}-.0871289{col 71}{space 3} -.030052
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0006628{col 30}{space 2} .0011202{col 41}{space 1}   -0.59{col 50}{space 3}0.554{col 58}{space 4}-.0028583{col 71}{space 3} .0015327
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1107394{col 30}{space 2} .0162557{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .0788788{col 71}{space 3} .1426001
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0820137{col 30}{space 2} .0427185{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4} -.001713{col 71}{space 3} .1657405
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5444153{col 30}{space 2} .0292372{col 41}{space 1}   18.62{col 50}{space 3}0.000{col 58}{space 4} .4871115{col 71}{space 3} .6017191
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6619414{col 30}{space 2} .0333231{col 41}{space 1}   19.86{col 50}{space 3}0.000{col 58}{space 4} .5966293{col 71}{space 3} .7272536
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1583652{col 30}{space 2} .0317919{col 41}{space 1}    4.98{col 50}{space 3}0.000{col 58}{space 4} .0960542{col 71}{space 3} .2206763
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1840577{col 30}{space 2} .0270444{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .1310517{col 71}{space 3} .2370637
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0234622{col 30}{space 2} .0092218{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0053879{col 71}{space 3} .0415366
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3661107{col 30}{space 2} .0352566{col 41}{space 1}  -10.38{col 50}{space 3}0.000{col 58}{space 4}-.4352125{col 71}{space 3} -.297009
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.544693{col 30}{space 2} .0343224{col 41}{space 1}  -45.01{col 50}{space 3}0.000{col 58}{space 4}-1.611964{col 71}{space 3}-1.477423
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4947564{col 30}{space 2} .0344971{col 41}{space 1}  -14.34{col 50}{space 3}0.000{col 58}{space 4}-.5623694{col 71}{space 3}-.4271433
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2901456{col 30}{space 2}  .034543{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.3578487{col 71}{space 3}-.2224425
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .390466{col 30}{space 2} .0443856{col 41}{space 1}    8.80{col 50}{space 3}0.000{col 58}{space 4} .3034718{col 71}{space 3} .4774603
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2015335{col 30}{space 2}  .047331{col 41}{space 1}   -4.26{col 50}{space 3}0.000{col 58}{space 4}-.2943006{col 71}{space 3}-.1087665
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0488026{col 30}{space 2} .0357596{col 41}{space 1}    1.36{col 50}{space 3}0.172{col 58}{space 4}-.0212849{col 71}{space 3} .1188901
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0931184{col 30}{space 2} .0401872{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0143531{col 71}{space 3} .1718838
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0409137{col 30}{space 2} .0364648{col 41}{space 1}    1.12{col 50}{space 3}0.262{col 58}{space 4} -.030556{col 71}{space 3} .1123834
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1332276{col 30}{space 2} .0403252{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0541916{col 71}{space 3} .2122636
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0759226{col 30}{space 2} .0410986{col 41}{space 1}   -1.85{col 50}{space 3}0.065{col 58}{space 4}-.1564744{col 71}{space 3} .0046293
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1942542{col 30}{space 2} .0392303{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1173642{col 71}{space 3} .2711442
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1504032{col 30}{space 2} .0611962{col 41}{space 1}   -2.46{col 50}{space 3}0.014{col 58}{space 4}-.2703455{col 71}{space 3} -.030461
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4954366{col 30}{space 2} .0412793{col 41}{space 1}   12.00{col 50}{space 3}0.000{col 58}{space 4} .4145308{col 71}{space 3} .5763425
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0376457{col 30}{space 2} .0401492{col 41}{space 1}    0.94{col 50}{space 3}0.348{col 58}{space 4}-.0410454{col 71}{space 3} .1163367
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.296415{col 30}{space 2} .0570654{col 41}{space 1}   75.29{col 50}{space 3}0.000{col 58}{space 4} 4.184569{col 71}{space 3} 4.408261
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78839319
         {txt}sigma_e {c |} {res} 1.2207153
             {txt}rho {c |} {res} .29434152{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0223                                         {txt}min = {res}         1
{txt}     between = {res}0.3144                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2061                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1922.47
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0589448{col 30}{space 2} .0115658{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .0362762{col 71}{space 3} .0816133
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0289763{col 30}{space 2} .0075645{col 41}{space 1}    3.83{col 50}{space 3}0.000{col 58}{space 4} .0141502{col 71}{space 3} .0438024
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0051673{col 30}{space 2} .0619364{col 41}{space 1}    0.08{col 50}{space 3}0.934{col 58}{space 4}-.1162258{col 71}{space 3} .1265603
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.002637{col 30}{space 2} .0010563{col 41}{space 1}   -2.50{col 50}{space 3}0.013{col 58}{space 4}-.0047073{col 71}{space 3}-.0005667
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0068882{col 30}{space 2}  .038642{col 41}{space 1}    0.18{col 50}{space 3}0.859{col 58}{space 4}-.0688488{col 71}{space 3} .0826252
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3224067{col 30}{space 2} .0321102{col 41}{space 1}   10.04{col 50}{space 3}0.000{col 58}{space 4} .2594719{col 71}{space 3} .3853416
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2298212{col 30}{space 2} .1626384{col 41}{space 1}   -1.41{col 50}{space 3}0.158{col 58}{space 4}-.5485866{col 71}{space 3} .0889443
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1748908{col 30}{space 2} .0381408{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4} .1001361{col 71}{space 3} .2496455
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1466601{col 30}{space 2} .0477094{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .0531515{col 71}{space 3} .2401688
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1179963{col 30}{space 2} .0717382{col 41}{space 1}    1.64{col 50}{space 3}0.100{col 58}{space 4} -.022608{col 71}{space 3} .2586006
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2098239{col 30}{space 2}  .052316{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .1072865{col 71}{space 3} .3123613
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1478757{col 30}{space 2} .0298434{col 41}{space 1}   -4.96{col 50}{space 3}0.000{col 58}{space 4}-.2063678{col 71}{space 3}-.0893837
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0083231{col 30}{space 2} .0036836{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0011034{col 71}{space 3} .0155429
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2150016{col 30}{space 2} .0312446{col 41}{space 1}    6.88{col 50}{space 3}0.000{col 58}{space 4} .1537633{col 71}{space 3} .2762399
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  1.00441{col 30}{space 2} .2820095{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .4516818{col 71}{space 3} 1.557139
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4291421{col 30}{space 2} .0592577{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .3129992{col 71}{space 3} .5452849
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4438928{col 30}{space 2} .0714272{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4}  .303898{col 71}{space 3} .5838877
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .390277{col 30}{space 2} .1159909{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4}  .162939{col 71}{space 3}  .617615
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1334388{col 30}{space 2} .0668842{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0023481{col 71}{space 3} .2645295
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0919019{col 30}{space 2} .0163183{col 41}{space 1}    5.63{col 50}{space 3}0.000{col 58}{space 4} .0599187{col 71}{space 3} .1238851
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1716763{col 30}{space 2} .0230519{col 41}{space 1}   -7.45{col 50}{space 3}0.000{col 58}{space 4}-.2168572{col 71}{space 3}-.1264954
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.917091{col 30}{space 2} .0813964{col 41}{space 1}   35.84{col 50}{space 3}0.000{col 58}{space 4} 2.757557{col 71}{space 3} 3.076625
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69784464
         {txt}sigma_e {c |} {res}  1.054425
             {txt}rho {c |} {res} .30459557{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0301                                         {txt}min = {res}         1
{txt}     between = {res}0.3898                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2567                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1222.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1182682{col 30}{space 2}  .020679{col 41}{space 1}    5.72{col 50}{space 3}0.000{col 58}{space 4}  .077738{col 71}{space 3} .1587984
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0095119{col 30}{space 2} .0118951{col 41}{space 1}   -0.80{col 50}{space 3}0.424{col 58}{space 4}-.0328258{col 71}{space 3}  .013802
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1891439{col 30}{space 2} .1127945{col 41}{space 1}   -1.68{col 50}{space 3}0.094{col 58}{space 4} -.410217{col 71}{space 3} .0319292
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0031706{col 30}{space 2} .0018078{col 41}{space 1}   -1.75{col 50}{space 3}0.079{col 58}{space 4}-.0067137{col 71}{space 3} .0003725
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1198441{col 30}{space 2}  .062972{col 41}{space 1}   -1.90{col 50}{space 3}0.057{col 58}{space 4} -.243267{col 71}{space 3} .0035788
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2793243{col 30}{space 2} .0603411{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .1610578{col 71}{space 3} .3975907
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3237906{col 30}{space 2} .2130752{col 41}{space 1}    1.52{col 50}{space 3}0.129{col 58}{space 4}-.0938292{col 71}{space 3} .7414104
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1137684{col 30}{space 2} .0719386{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4}-.0272287{col 71}{space 3} .2547654
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2162074{col 30}{space 2}   .16985{col 41}{space 1}    1.27{col 50}{space 3}0.203{col 58}{space 4}-.1166924{col 71}{space 3} .5491073
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1278051{col 30}{space 2} .0867178{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0421587{col 71}{space 3} .2977689
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2279242{col 30}{space 2} .0604498{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .1094447{col 71}{space 3} .3464037
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1665101{col 30}{space 2} .0453624{col 41}{space 1}   -3.67{col 50}{space 3}0.000{col 58}{space 4}-.2554187{col 71}{space 3}-.0776014
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0317192{col 30}{space 2} .0317153{col 41}{space 1}    1.00{col 50}{space 3}0.317{col 58}{space 4}-.0304417{col 71}{space 3} .0938801
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0326442{col 30}{space 2} .0614198{col 41}{space 1}    0.53{col 50}{space 3}0.595{col 58}{space 4}-.0877365{col 71}{space 3} .1530248
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0401583{col 30}{space 2} .3255209{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4}-.5978511{col 71}{space 3} .6781676
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6763701{col 30}{space 2} .1154629{col 41}{space 1}    5.86{col 50}{space 3}0.000{col 58}{space 4} .4500669{col 71}{space 3} .9026733
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.072576{col 30}{space 2} .2173871{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .6465055{col 71}{space 3} 1.498647
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4661511{col 30}{space 2} .1286073{col 41}{space 1}    3.62{col 50}{space 3}0.000{col 58}{space 4} .2140853{col 71}{space 3} .7182168
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3833945{col 30}{space 2} .1088439{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4} .1700643{col 71}{space 3} .5967247
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0558382{col 30}{space 2} .0367879{col 41}{space 1}    1.52{col 50}{space 3}0.129{col 58}{space 4}-.0162647{col 71}{space 3} .1279411
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2443865{col 30}{space 2} .0569639{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .1327394{col 71}{space 3} .3560336
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0949789{col 30}{space 2} .0526638{col 41}{space 1}    1.80{col 50}{space 3}0.071{col 58}{space 4}-.0082402{col 71}{space 3} .1981981
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.640998{col 30}{space 2} .1598697{col 41}{space 1}   29.03{col 50}{space 3}0.000{col 58}{space 4} 4.327659{col 71}{space 3} 4.954337
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72511651
         {txt}sigma_e {c |} {res} 1.2913593
             {txt}rho {c |} {res}  .2397161{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0543                                         {txt}min = {res}         1
{txt}     between = {res}0.1711                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1329                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}   863.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2845619{col 30}{space 2} .0396951{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4}  .206761{col 71}{space 3} .3623627
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0086647{col 30}{space 2}  .007309{col 41}{space 1}    1.19{col 50}{space 3}0.236{col 58}{space 4}-.0056607{col 71}{space 3} .0229902
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0878382{col 30}{space 2} .1165593{col 41}{space 1}   -0.75{col 50}{space 3}0.451{col 58}{space 4}-.3162902{col 71}{space 3} .1406138
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0033631{col 30}{space 2} .0015608{col 41}{space 1}    2.15{col 50}{space 3}0.031{col 58}{space 4} .0003039{col 71}{space 3} .0064222
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0849703{col 30}{space 2} .0695062{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0512594{col 71}{space 3}    .2212
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2927265{col 30}{space 2} .0511653{col 41}{space 1}    5.72{col 50}{space 3}0.000{col 58}{space 4} .1924443{col 71}{space 3} .3930086
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3876615{col 30}{space 2}  .143737{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .1059422{col 71}{space 3} .6693808
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0512676{col 30}{space 2} .0854755{col 41}{space 1}    0.60{col 50}{space 3}0.549{col 58}{space 4}-.1162613{col 71}{space 3} .2187965
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2285361{col 30}{space 2} .1785527{col 41}{space 1}    1.28{col 50}{space 3}0.201{col 58}{space 4}-.1214207{col 71}{space 3} .5784929
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2649388{col 30}{space 2} .1071774{col 41}{space 1}    2.47{col 50}{space 3}0.013{col 58}{space 4} .0548749{col 71}{space 3} .4750027
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2220909{col 30}{space 2}  .076119{col 41}{space 1}   -2.92{col 50}{space 3}0.004{col 58}{space 4}-.3712814{col 71}{space 3}-.0729004
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1327876{col 30}{space 2} .0460201{col 41}{space 1}   -2.89{col 50}{space 3}0.004{col 58}{space 4}-.2229853{col 71}{space 3}-.0425899
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014772{col 30}{space 2} .0015616{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.0045379{col 71}{space 3} .0015834
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2619271{col 30}{space 2} .2131243{col 41}{space 1}    1.23{col 50}{space 3}0.219{col 58}{space 4}-.1557888{col 71}{space 3} .6796431
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0259992{col 30}{space 2} .1719357{col 41}{space 1}    0.15{col 50}{space 3}0.880{col 58}{space 4}-.3109885{col 71}{space 3} .3629869
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3299828{col 30}{space 2} .1033121{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .1274949{col 71}{space 3} .5324708
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6530057{col 30}{space 2} .1934741{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .2738034{col 71}{space 3} 1.032208
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0531449{col 30}{space 2} .1333683{col 41}{space 1}    0.40{col 50}{space 3}0.690{col 58}{space 4}-.2082521{col 71}{space 3}  .314542
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5025105{col 30}{space 2} .0933661{col 41}{space 1}    5.38{col 50}{space 3}0.000{col 58}{space 4} .3195163{col 71}{space 3} .6855046
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2012858{col 30}{space 2} .0473094{col 41}{space 1}   -4.25{col 50}{space 3}0.000{col 58}{space 4}-.2940106{col 71}{space 3}-.1085611
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2857811{col 30}{space 2} .0435441{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .2004363{col 71}{space 3} .3711259
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.303788{col 30}{space 2}  .126513{col 41}{space 1}   34.02{col 50}{space 3}0.000{col 58}{space 4} 4.055827{col 71}{space 3} 4.551749
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .52787586
         {txt}sigma_e {c |} {res} 1.4243525
             {txt}rho {c |} {res} .12076318{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0388                                         {txt}min = {res}         1
{txt}     between = {res}0.2949                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2521                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3406.76
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .118953{col 30}{space 2}  .018043{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4} .0835893{col 71}{space 3} .1543166
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0356447{col 30}{space 2} .0049515{col 41}{space 1}   -7.20{col 50}{space 3}0.000{col 58}{space 4}-.0453494{col 71}{space 3}-.0259399
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1829734{col 30}{space 2} .0595249{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .0663067{col 71}{space 3}   .29964
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0058748{col 30}{space 2} .0010448{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4}  .003827{col 71}{space 3} .0079225
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3232655{col 30}{space 2} .0430733{col 41}{space 1}    7.51{col 50}{space 3}0.000{col 58}{space 4} .2388435{col 71}{space 3} .4076876
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1965939{col 30}{space 2} .0299731{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1378477{col 71}{space 3} .2553401
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0156521{col 30}{space 2} .0456989{col 41}{space 1}   -0.34{col 50}{space 3}0.732{col 58}{space 4}-.1052203{col 71}{space 3} .0739162
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1467751{col 30}{space 2} .0438832{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4} .0607657{col 71}{space 3} .2327846
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .063071{col 30}{space 2} .0566449{col 41}{space 1}    1.11{col 50}{space 3}0.266{col 58}{space 4}-.0479511{col 71}{space 3}  .174093
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2507772{col 30}{space 2} .0674271{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .1186226{col 71}{space 3} .3829319
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3087119{col 30}{space 2} .0472495{col 41}{space 1}    6.53{col 50}{space 3}0.000{col 58}{space 4} .2161046{col 71}{space 3} .4013191
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .062388{col 30}{space 2} .0483862{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.0324471{col 71}{space 3} .1572231
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0081243{col 30}{space 2} .0067739{col 41}{space 1}   -1.20{col 50}{space 3}0.230{col 58}{space 4}-.0214009{col 71}{space 3} .0051523
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3323829{col 30}{space 2} .0612006{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .2124319{col 71}{space 3} .4523338
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1328787{col 30}{space 2} .0607031{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0139028{col 71}{space 3} .2518547
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7496372{col 30}{space 2}  .063843{col 41}{space 1}   11.74{col 50}{space 3}0.000{col 58}{space 4} .6245072{col 71}{space 3} .8747672
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8423967{col 30}{space 2} .0682609{col 41}{space 1}   12.34{col 50}{space 3}0.000{col 58}{space 4} .7086077{col 71}{space 3} .9761857
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1203319{col 30}{space 2} .0854462{col 41}{space 1}    1.41{col 50}{space 3}0.159{col 58}{space 4}-.0471395{col 71}{space 3} .2878033
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0479603{col 30}{space 2} .0595283{col 41}{space 1}   -0.81{col 50}{space 3}0.420{col 58}{space 4}-.1646335{col 71}{space 3}  .068713
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.055539{col 30}{space 2}  .024501{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4}-.1035601{col 71}{space 3}-.0075179
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5608958{col 30}{space 2} .0360377{col 41}{space 1}  -15.56{col 50}{space 3}0.000{col 58}{space 4}-.6315284{col 71}{space 3}-.4902632
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5437961{col 30}{space 2}  .036652{col 41}{space 1}  -14.84{col 50}{space 3}0.000{col 58}{space 4}-.6156327{col 71}{space 3}-.4719595
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3823686{col 30}{space 2} .0366266{col 41}{space 1}  -10.44{col 50}{space 3}0.000{col 58}{space 4}-.4541555{col 71}{space 3}-.3105817
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.405869{col 30}{space 2}   .08793{col 41}{space 1}   50.11{col 50}{space 3}0.000{col 58}{space 4} 4.233529{col 71}{space 3} 4.578209
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85047436
         {txt}sigma_e {c |} {res} 1.2178573
             {txt}rho {c |} {res} .32780974{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0448                                         {txt}min = {res}         1
{txt}     between = {res}0.2285                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1823                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1867.81
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2061141{col 30}{space 2} .0147184{col 41}{space 1}   14.00{col 50}{space 3}0.000{col 58}{space 4} .1772665{col 71}{space 3} .2349617
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0140444{col 30}{space 2} .0055595{col 41}{space 1}   -2.53{col 50}{space 3}0.012{col 58}{space 4}-.0249408{col 71}{space 3}-.0031479
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0200582{col 30}{space 2} .0684788{col 41}{space 1}   -0.29{col 50}{space 3}0.770{col 58}{space 4}-.1542741{col 71}{space 3} .1141578
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0018438{col 30}{space 2} .0011041{col 41}{space 1}   -1.67{col 50}{space 3}0.095{col 58}{space 4}-.0040078{col 71}{space 3} .0003202
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0380984{col 30}{space 2} .0393627{col 41}{space 1}    0.97{col 50}{space 3}0.333{col 58}{space 4}-.0390511{col 71}{space 3} .1152478
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2576911{col 30}{space 2} .0361958{col 41}{space 1}    7.12{col 50}{space 3}0.000{col 58}{space 4} .1867487{col 71}{space 3} .3286335
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2132648{col 30}{space 2} .0893311{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0381791{col 71}{space 3} .3883505
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2542314{col 30}{space 2} .0490046{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .1581841{col 71}{space 3} .3502786
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0521171{col 30}{space 2} .0576178{col 41}{space 1}    0.90{col 50}{space 3}0.366{col 58}{space 4}-.0608118{col 71}{space 3} .1650459
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1253565{col 30}{space 2}  .039429{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .0480771{col 71}{space 3} .2026359
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1958058{col 30}{space 2} .0417557{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4}  .113966{col 71}{space 3} .2776455
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1655628{col 30}{space 2} .0349964{col 41}{space 1}   -4.73{col 50}{space 3}0.000{col 58}{space 4}-.2341544{col 71}{space 3}-.0969711
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0027803{col 30}{space 2} .0032661{col 41}{space 1}   -0.85{col 50}{space 3}0.395{col 58}{space 4}-.0091818{col 71}{space 3} .0036212
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0189455{col 30}{space 2} .0328124{col 41}{space 1}    0.58{col 50}{space 3}0.564{col 58}{space 4}-.0453657{col 71}{space 3} .0832567
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3296402{col 30}{space 2} .1203773{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0937051{col 71}{space 3} .5655752
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4361774{col 30}{space 2} .0675786{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .3037257{col 71}{space 3}  .568629
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .512806{col 30}{space 2} .0791238{col 41}{space 1}    6.48{col 50}{space 3}0.000{col 58}{space 4} .3577262{col 71}{space 3} .6678857
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0094275{col 30}{space 2}  .057479{col 41}{space 1}   -0.16{col 50}{space 3}0.870{col 58}{space 4}-.1220843{col 71}{space 3} .1032293
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3255859{col 30}{space 2} .0596303{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .2087126{col 71}{space 3} .4424592
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0759636{col 30}{space 2} .0191563{col 41}{space 1}   -3.97{col 50}{space 3}0.000{col 58}{space 4}-.1135093{col 71}{space 3}-.0384179
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0334623{col 30}{space 2} .0384338{col 41}{space 1}   -0.87{col 50}{space 3}0.384{col 58}{space 4}-.1087911{col 71}{space 3} .0418665
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0393082{col 30}{space 2}  .033222{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0258057{col 71}{space 3} .1044221
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0092952{col 30}{space 2} .0375401{col 41}{space 1}    0.25{col 50}{space 3}0.804{col 58}{space 4}-.0642821{col 71}{space 3} .0828725
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.351451{col 30}{space 2} .0899575{col 41}{space 1}   48.37{col 50}{space 3}0.000{col 58}{space 4} 4.175137{col 71}{space 3} 4.527764
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75449723
         {txt}sigma_e {c |} {res} 1.1916698
             {txt}rho {c |} {res} .28615783{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0494                                         {txt}min = {res}         1
{txt}     between = {res}0.2926                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1948                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2405.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1133799{col 30}{space 2} .0128289{col 41}{space 1}    8.84{col 50}{space 3}0.000{col 58}{space 4} .0882357{col 71}{space 3} .1385241
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0009886{col 30}{space 2} .0056306{col 41}{space 1}    0.18{col 50}{space 3}0.861{col 58}{space 4}-.0100472{col 71}{space 3} .0120244
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0122374{col 30}{space 2} .0610935{col 41}{space 1}    0.20{col 50}{space 3}0.841{col 58}{space 4}-.1075036{col 71}{space 3} .1319783
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006444{col 30}{space 2} .0010587{col 41}{space 1}   -0.61{col 50}{space 3}0.543{col 58}{space 4}-.0027195{col 71}{space 3} .0014307
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0578811{col 30}{space 2} .0350345{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0107853{col 71}{space 3} .1265474
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3318651{col 30}{space 2} .0348265{col 41}{space 1}    9.53{col 50}{space 3}0.000{col 58}{space 4} .2636064{col 71}{space 3} .4001239
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2172907{col 30}{space 2} .0574827{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .1046266{col 71}{space 3} .3299547
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2342785{col 30}{space 2} .0381482{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .1595095{col 71}{space 3} .3090475
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3507372{col 30}{space 2} .0385959{col 41}{space 1}    9.09{col 50}{space 3}0.000{col 58}{space 4} .2750905{col 71}{space 3} .4263838
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0402075{col 30}{space 2} .0311194{col 41}{space 1}    1.29{col 50}{space 3}0.196{col 58}{space 4}-.0207854{col 71}{space 3} .1012004
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1903382{col 30}{space 2}  .032846{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1259612{col 71}{space 3} .2547151
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0100893{col 30}{space 2} .0253089{col 41}{space 1}   -0.40{col 50}{space 3}0.690{col 58}{space 4}-.0596939{col 71}{space 3} .0395153
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0008982{col 30}{space 2} .0016115{col 41}{space 1}    0.56{col 50}{space 3}0.577{col 58}{space 4}-.0022602{col 71}{space 3} .0040567
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0178959{col 30}{space 2} .0277101{col 41}{space 1}    0.65{col 50}{space 3}0.518{col 58}{space 4}-.0364149{col 71}{space 3} .0722067
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1700012{col 30}{space 2} .0889263{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0042911{col 71}{space 3} .3442935
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3435957{col 30}{space 2} .0636995{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4}  .218747{col 71}{space 3} .4684445
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2660178{col 30}{space 2} .0720002{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .1248999{col 71}{space 3} .4071356
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1927726{col 30}{space 2} .0573505{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4} .0803677{col 71}{space 3} .3051775
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3112828{col 30}{space 2} .0555666{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .2023743{col 71}{space 3} .4201913
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1326024{col 30}{space 2} .0224117{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0886762{col 71}{space 3} .1765285
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1665538{col 30}{space 2} .0401092{col 41}{space 1}   -4.15{col 50}{space 3}0.000{col 58}{space 4}-.2451663{col 71}{space 3}-.0879413
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1000995{col 30}{space 2} .0349958{col 41}{space 1}   -2.86{col 50}{space 3}0.004{col 58}{space 4}  -.16869{col 71}{space 3}-.0315091
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .336881{col 30}{space 2} .0350333{col 41}{space 1}    9.62{col 50}{space 3}0.000{col 58}{space 4}  .268217{col 71}{space 3}  .405545
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0834614{col 30}{space 2} .0352447{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0143831{col 71}{space 3} .1525397
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3101497{col 30}{space 2} .0325335{col 41}{space 1}    9.53{col 50}{space 3}0.000{col 58}{space 4} .2463852{col 71}{space 3} .3739143
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.530111{col 30}{space 2} .0996003{col 41}{space 1}   35.44{col 50}{space 3}0.000{col 58}{space 4} 3.334898{col 71}{space 3} 3.725324
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75732817
         {txt}sigma_e {c |} {res} 1.2447709
             {txt}rho {c |} {res} .27015818{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. 
. esttab using  S15_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons )
{res}{txt}(note: file S15_farmer.rtf not found)
(output written to {browse  `"S15_farmer.rtf"'})

{com}. 
. 
. 
. 
. 
. *                          vill_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0221                                         {txt}min = {res}         1
{txt}     between = {res}0.3684                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2785                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 17516.99
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0490773{col 30}{space 2} .0077957{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4}  .033798{col 71}{space 3} .0643566
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0531661{col 30}{space 2} .0028414{col 41}{space 1}  -18.71{col 50}{space 3}0.000{col 58}{space 4}-.0587353{col 71}{space 3} -.047597
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0008043{col 30}{space 2} .0025508{col 41}{space 1}   -0.32{col 50}{space 3}0.753{col 58}{space 4}-.0058038{col 71}{space 3} .0041951
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0148025{col 30}{space 2} .0298534{col 41}{space 1}    0.50{col 50}{space 3}0.620{col 58}{space 4}-.0437091{col 71}{space 3} .0733141
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0003675{col 30}{space 2} .0004909{col 41}{space 1}    0.75{col 50}{space 3}0.454{col 58}{space 4}-.0005945{col 71}{space 3} .0013296
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0237828{col 30}{space 2} .0181744{col 41}{space 1}    1.31{col 50}{space 3}0.191{col 58}{space 4}-.0118384{col 71}{space 3} .0594041
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .289271{col 30}{space 2} .0154574{col 41}{space 1}   18.71{col 50}{space 3}0.000{col 58}{space 4}  .258975{col 71}{space 3} .3195671
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1032695{col 30}{space 2} .0317837{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .0409746{col 71}{space 3} .1655645
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1677256{col 30}{space 2} .0201316{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .1282683{col 71}{space 3} .2071829
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1551179{col 30}{space 2} .0243934{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .1073077{col 71}{space 3} .2029282
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1351407{col 30}{space 2} .0211513{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4}  .093685{col 71}{space 3} .1765964
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2044231{col 30}{space 2} .0193155{col 41}{space 1}   10.58{col 50}{space 3}0.000{col 58}{space 4} .1665655{col 71}{space 3} .2422807
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0372066{col 30}{space 2} .0146243{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.0658697{col 71}{space 3}-.0085435
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006045{col 30}{space 2} .0010981{col 41}{space 1}    0.55{col 50}{space 3}0.582{col 58}{space 4}-.0015479{col 71}{space 3} .0027568
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1463896{col 30}{space 2} .0162005{col 41}{space 1}    9.04{col 50}{space 3}0.000{col 58}{space 4} .1146371{col 71}{space 3}  .178142
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0828357{col 30}{space 2} .0424717{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0004074{col 71}{space 3} .1660787
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5124244{col 30}{space 2} .0292833{col 41}{space 1}   17.50{col 50}{space 3}0.000{col 58}{space 4} .4550301{col 71}{space 3} .5698187
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .571536{col 30}{space 2} .0332252{col 41}{space 1}   17.20{col 50}{space 3}0.000{col 58}{space 4} .5064159{col 71}{space 3} .6366562
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0852032{col 30}{space 2}  .031868{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4}  .022743{col 71}{space 3} .1476634
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1444147{col 30}{space 2} .0270225{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .0914516{col 71}{space 3} .1973778
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1012482{col 30}{space 2}  .010017{col 41}{space 1}   10.11{col 50}{space 3}0.000{col 58}{space 4} .0816151{col 71}{space 3} .1208812
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.6078943{col 30}{space 2} .0372946{col 41}{space 1}  -16.30{col 50}{space 3}0.000{col 58}{space 4}-.6809904{col 71}{space 3}-.5347981
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.836582{col 30}{space 2} .0377604{col 41}{space 1}  -48.64{col 50}{space 3}0.000{col 58}{space 4}-1.910591{col 71}{space 3}-1.762573
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.8026584{col 30}{space 2}  .038454{col 41}{space 1}  -20.87{col 50}{space 3}0.000{col 58}{space 4}-.8780269{col 71}{space 3}-.7272899
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.7393509{col 30}{space 2} .0423682{col 41}{space 1}  -17.45{col 50}{space 3}0.000{col 58}{space 4}-.8223911{col 71}{space 3}-.6563107
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1741624{col 30}{space 2} .0458116{col 41}{space 1}    3.80{col 50}{space 3}0.000{col 58}{space 4} .0843733{col 71}{space 3} .2639516
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2259646{col 30}{space 2} .0476892{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4}-.3194338{col 71}{space 3}-.1324954
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0824888{col 30}{space 2}  .036237{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0114655{col 71}{space 3} .1535121
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}  .098592{col 30}{space 2} .0406513{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0189169{col 71}{space 3} .1782672
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0588511{col 30}{space 2} .0368465{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0133668{col 71}{space 3} .1310689
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1559447{col 30}{space 2} .0409028{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .0757766{col 71}{space 3} .2361127
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0554067{col 30}{space 2} .0418254{col 41}{space 1}   -1.32{col 50}{space 3}0.185{col 58}{space 4} -.137383{col 71}{space 3} .0265695
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .219844{col 30}{space 2} .0396893{col 41}{space 1}    5.54{col 50}{space 3}0.000{col 58}{space 4} .1420543{col 71}{space 3} .2976336
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2195303{col 30}{space 2} .0612248{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.3395288{col 71}{space 3}-.0995319
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4795908{col 30}{space 2} .0415511{col 41}{space 1}   11.54{col 50}{space 3}0.000{col 58}{space 4} .3981521{col 71}{space 3} .5610295
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0253642{col 30}{space 2} .0405914{col 41}{space 1}    0.62{col 50}{space 3}0.532{col 58}{space 4}-.0541935{col 71}{space 3} .1049219
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.693887{col 30}{space 2} .0685076{col 41}{space 1}   68.52{col 50}{space 3}0.000{col 58}{space 4} 4.559614{col 71}{space 3} 4.828159
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .77379395
         {txt}sigma_e {c |} {res} 1.2264047
             {txt}rho {c |} {res} .28473932{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0178                                         {txt}min = {res}         1
{txt}     between = {res}0.3197                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2058                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1967.28
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0508988{col 30}{space 2} .0161908{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0191654{col 71}{space 3} .0826322
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0469849{col 30}{space 2} .0096609{col 41}{space 1}   -4.86{col 50}{space 3}0.000{col 58}{space 4}-.0659199{col 71}{space 3}-.0280499
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0513423{col 30}{space 2} .0074289{col 41}{space 1}    6.91{col 50}{space 3}0.000{col 58}{space 4} .0367818{col 71}{space 3} .0659027
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0266394{col 30}{space 2} .0620218{col 41}{space 1}   -0.43{col 50}{space 3}0.668{col 58}{space 4}-.1481999{col 71}{space 3}  .094921
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023284{col 30}{space 2} .0010498{col 41}{space 1}   -2.22{col 50}{space 3}0.027{col 58}{space 4} -.004386{col 71}{space 3}-.0002708
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0393665{col 30}{space 2} .0386327{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.1150853{col 71}{space 3} .0363522
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3258532{col 30}{space 2} .0322104{col 41}{space 1}   10.12{col 50}{space 3}0.000{col 58}{space 4}  .262722{col 71}{space 3} .3889844
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2155577{col 30}{space 2} .1614261{col 41}{space 1}   -1.34{col 50}{space 3}0.182{col 58}{space 4}-.5319471{col 71}{space 3} .1008316
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1759073{col 30}{space 2}  .038191{col 41}{space 1}    4.61{col 50}{space 3}0.000{col 58}{space 4} .1010543{col 71}{space 3} .2507603
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1571486{col 30}{space 2}  .047905{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .0632565{col 71}{space 3} .2510406
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1063103{col 30}{space 2} .0716375{col 41}{space 1}    1.48{col 50}{space 3}0.138{col 58}{space 4}-.0340966{col 71}{space 3} .2467172
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .205716{col 30}{space 2} .0524411{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1029332{col 71}{space 3} .3084987
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1246686{col 30}{space 2} .0300726{col 41}{space 1}   -4.15{col 50}{space 3}0.000{col 58}{space 4}-.1836098{col 71}{space 3}-.0657275
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0145011{col 30}{space 2} .0037911{col 41}{space 1}    3.83{col 50}{space 3}0.000{col 58}{space 4} .0070706{col 71}{space 3} .0219315
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2377306{col 30}{space 2} .0316506{col 41}{space 1}    7.51{col 50}{space 3}0.000{col 58}{space 4} .1756965{col 71}{space 3} .2997648
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9096421{col 30}{space 2} .2772216{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .3662979{col 71}{space 3} 1.452986
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4472429{col 30}{space 2}  .059169{col 41}{space 1}    7.56{col 50}{space 3}0.000{col 58}{space 4} .3312737{col 71}{space 3} .5632121
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3173297{col 30}{space 2}  .071982{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .1762475{col 71}{space 3} .4584119
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3210259{col 30}{space 2} .1148996{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0958269{col 71}{space 3} .5462249
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .089285{col 30}{space 2} .0669279{col 41}{space 1}    1.33{col 50}{space 3}0.182{col 58}{space 4}-.0418913{col 71}{space 3} .2204613
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1059502{col 30}{space 2} .0198389{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .0670666{col 71}{space 3} .1448337
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1581719{col 30}{space 2} .0231221{col 41}{space 1}   -6.84{col 50}{space 3}0.000{col 58}{space 4}-.2034904{col 71}{space 3}-.1128533
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.884782{col 30}{space 2} .1284404{col 41}{space 1}   22.46{col 50}{space 3}0.000{col 58}{space 4} 2.633043{col 71}{space 3} 3.136521
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69276021
         {txt}sigma_e {c |} {res} 1.0562685
             {txt}rho {c |} {res} .30077135{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0181                                         {txt}min = {res}         1
{txt}     between = {res}0.3973                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2520                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1258.65
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0542838{col 30}{space 2}  .027859{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0003187{col 71}{space 3} .1088863
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.058526{col 30}{space 2} .0123875{col 41}{space 1}   -4.72{col 50}{space 3}0.000{col 58}{space 4} -.082805{col 71}{space 3} -.034247
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0027081{col 30}{space 2} .0119209{col 41}{space 1}   -0.23{col 50}{space 3}0.820{col 58}{space 4}-.0260726{col 71}{space 3} .0206564
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1660038{col 30}{space 2} .1127375{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4}-.3869651{col 71}{space 3} .0549576
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025006{col 30}{space 2} .0017936{col 41}{space 1}   -1.39{col 50}{space 3}0.163{col 58}{space 4} -.006016{col 71}{space 3} .0010148
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1173542{col 30}{space 2} .0632695{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-.2413601{col 71}{space 3} .0066517
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3091345{col 30}{space 2} .0607367{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .1900927{col 71}{space 3} .4281762
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3007012{col 30}{space 2}  .212803{col 41}{space 1}    1.41{col 50}{space 3}0.158{col 58}{space 4} -.116385{col 71}{space 3} .7177873
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1238186{col 30}{space 2}  .072203{col 41}{space 1}    1.71{col 50}{space 3}0.086{col 58}{space 4}-.0176967{col 71}{space 3} .2653338
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2176663{col 30}{space 2} .1678253{col 41}{space 1}    1.30{col 50}{space 3}0.195{col 58}{space 4}-.1112653{col 71}{space 3} .5465979
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .118019{col 30}{space 2} .0881898{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0548298{col 71}{space 3} .2908677
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2393231{col 30}{space 2} .0605874{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4}  .120574{col 71}{space 3} .3580723
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1458225{col 30}{space 2} .0453532{col 41}{space 1}   -3.22{col 50}{space 3}0.001{col 58}{space 4}-.2347132{col 71}{space 3}-.0569318
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1008151{col 30}{space 2} .0357188{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .0308076{col 71}{space 3} .1708225
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0983169{col 30}{space 2}   .06263{col 41}{space 1}    1.57{col 50}{space 3}0.116{col 58}{space 4}-.0244356{col 71}{space 3} .2210695
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2375394{col 30}{space 2} .3332154{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4}-.4155507{col 71}{space 3} .8906295
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6531128{col 30}{space 2} .1159916{col 41}{space 1}    5.63{col 50}{space 3}0.000{col 58}{space 4} .4257735{col 71}{space 3} .8804522
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .688843{col 30}{space 2} .2181033{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .2613683{col 71}{space 3} 1.116318
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3034902{col 30}{space 2} .1304479{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4}  .047817{col 71}{space 3} .5591635
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2973915{col 30}{space 2} .1081178{col 41}{space 1}    2.75{col 50}{space 3}0.006{col 58}{space 4} .0854844{col 71}{space 3} .5092986
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0249555{col 30}{space 2} .0450883{col 41}{space 1}   -0.55{col 50}{space 3}0.580{col 58}{space 4} -.113327{col 71}{space 3}  .063416
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .4017015{col 30}{space 2} .0698607{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .2647771{col 71}{space 3} .5386259
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1363718{col 30}{space 2} .0536794{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0311622{col 71}{space 3} .2415814
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.586779{col 30}{space 2} .2562447{col 41}{space 1}   21.80{col 50}{space 3}0.000{col 58}{space 4} 5.084549{col 71}{space 3} 6.089009
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70800261
         {txt}sigma_e {c |} {res} 1.2968922
             {txt}rho {c |} {res} .22960258{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0363                                         {txt}min = {res}         1
{txt}     between = {res}0.1942                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1410                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   939.55
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1649157{col 30}{space 2}  .035878{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4}  .094596{col 71}{space 3} .2352353
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0661285{col 30}{space 2} .0075016{col 41}{space 1}   -8.82{col 50}{space 3}0.000{col 58}{space 4}-.0808314{col 71}{space 3}-.0514255
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0136513{col 30}{space 2}  .007012{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4}-.0000919{col 71}{space 3} .0273946
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0219776{col 30}{space 2} .1156036{col 41}{space 1}   -0.19{col 50}{space 3}0.849{col 58}{space 4}-.2485565{col 71}{space 3} .2046014
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0017338{col 30}{space 2} .0015615{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-.0013267{col 71}{space 3} .0047943
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .022685{col 30}{space 2} .0680325{col 41}{space 1}    0.33{col 50}{space 3}0.739{col 58}{space 4}-.1106563{col 71}{space 3} .1560262
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2868066{col 30}{space 2} .0510018{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .1868449{col 71}{space 3} .3867684
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4345089{col 30}{space 2} .1457487{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .1488467{col 71}{space 3}  .720171
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0761989{col 30}{space 2} .0866412{col 41}{space 1}    0.88{col 50}{space 3}0.379{col 58}{space 4}-.0936147{col 71}{space 3} .2460124
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}    .1157{col 30}{space 2} .1829494{col 41}{space 1}    0.63{col 50}{space 3}0.527{col 58}{space 4}-.2428743{col 71}{space 3} .4742742
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2801304{col 30}{space 2} .1084667{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .0675396{col 71}{space 3} .4927211
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2039948{col 30}{space 2} .0778667{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4}-.3566108{col 71}{space 3}-.0513788
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0794257{col 30}{space 2} .0463214{col 41}{space 1}   -1.71{col 50}{space 3}0.086{col 58}{space 4}-.1702139{col 71}{space 3} .0113626
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0009544{col 30}{space 2} .0015016{col 41}{space 1}   -0.64{col 50}{space 3}0.525{col 58}{space 4}-.0038975{col 71}{space 3} .0019887
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2735177{col 30}{space 2} .2185912{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.1549131{col 71}{space 3} .7019485
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0621051{col 30}{space 2}  .173198{col 41}{space 1}   -0.36{col 50}{space 3}0.720{col 58}{space 4}-.4015668{col 71}{space 3} .2773567
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1605905{col 30}{space 2}  .104883{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0449764{col 71}{space 3} .3661575
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .416827{col 30}{space 2} .2013993{col 41}{space 1}    2.07{col 50}{space 3}0.038{col 58}{space 4} .0220917{col 71}{space 3} .8115623
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1221766{col 30}{space 2} .1346127{col 41}{space 1}   -0.91{col 50}{space 3}0.364{col 58}{space 4}-.3860126{col 71}{space 3} .1416595
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4291361{col 30}{space 2}  .095154{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .2426377{col 71}{space 3} .6156344
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0752473{col 30}{space 2}  .040964{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.1555352{col 71}{space 3} .0050406
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .3094496{col 30}{space 2} .0443197{col 41}{space 1}    6.98{col 50}{space 3}0.000{col 58}{space 4} .2225845{col 71}{space 3} .3963147
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.216281{col 30}{space 2} .1662346{col 41}{space 1}   31.38{col 50}{space 3}0.000{col 58}{space 4} 4.890467{col 71}{space 3} 5.542094
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .46365282
         {txt}sigma_e {c |} {res} 1.4347853
             {txt}rho {c |} {res} .09455293{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0352                                         {txt}min = {res}         1
{txt}     between = {res}0.3239                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2742                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3970.60
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0593638{col 30}{space 2} .0178991{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0242823{col 71}{space 3} .0944454
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.110532{col 30}{space 2}  .008487{col 41}{space 1}  -13.02{col 50}{space 3}0.000{col 58}{space 4}-.1271663{col 71}{space 3}-.0938977
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0217426{col 30}{space 2} .0049348{col 41}{space 1}   -4.41{col 50}{space 3}0.000{col 58}{space 4}-.0314148{col 71}{space 3}-.0120705
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1701575{col 30}{space 2} .0588708{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0547729{col 71}{space 3} .2855422
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0035725{col 30}{space 2} .0010283{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .0015571{col 71}{space 3} .0055878
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2695423{col 30}{space 2} .0428266{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1856037{col 71}{space 3} .3534809
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1825384{col 30}{space 2} .0296441{col 41}{space 1}    6.16{col 50}{space 3}0.000{col 58}{space 4}  .124437{col 71}{space 3} .2406397
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0180641{col 30}{space 2} .0455942{col 41}{space 1}   -0.40{col 50}{space 3}0.692{col 58}{space 4}-.1074271{col 71}{space 3} .0712988
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1448179{col 30}{space 2} .0439142{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0587477{col 71}{space 3} .2308881
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0618287{col 30}{space 2} .0568785{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.0496511{col 71}{space 3} .1733084
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2380499{col 30}{space 2} .0671323{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4}  .106473{col 71}{space 3} .3696267
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3019889{col 30}{space 2} .0473032{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .2092763{col 71}{space 3} .3947016
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0877643{col 30}{space 2} .0478459{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4} -.006012{col 71}{space 3} .1815406
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0043927{col 30}{space 2} .0053574{col 41}{space 1}   -0.82{col 50}{space 3}0.412{col 58}{space 4} -.014893{col 71}{space 3} .0061076
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2986317{col 30}{space 2} .0607698{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4} .1795251{col 71}{space 3} .4177383
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1419844{col 30}{space 2} .0599628{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0244595{col 71}{space 3} .2595092
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6473354{col 30}{space 2} .0636004{col 41}{space 1}   10.18{col 50}{space 3}0.000{col 58}{space 4} .5226809{col 71}{space 3} .7719899
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6977781{col 30}{space 2} .0683243{col 41}{space 1}   10.21{col 50}{space 3}0.000{col 58}{space 4}  .563865{col 71}{space 3} .8316912
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0894817{col 30}{space 2} .0847598{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0766445{col 71}{space 3}  .255608
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0584376{col 30}{space 2} .0589049{col 41}{space 1}   -0.99{col 50}{space 3}0.321{col 58}{space 4} -.173889{col 71}{space 3} .0570138
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1613385{col 30}{space 2} .0221686{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .1178889{col 71}{space 3} .2047881
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.4987147{col 30}{space 2} .0357517{col 41}{space 1}  -13.95{col 50}{space 3}0.000{col 58}{space 4}-.5687868{col 71}{space 3}-.4286427
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.506391{col 30}{space 2}  .036256{col 41}{space 1}  -13.97{col 50}{space 3}0.000{col 58}{space 4}-.5774514{col 71}{space 3}-.4353305
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3712427{col 30}{space 2} .0365032{col 41}{space 1}  -10.17{col 50}{space 3}0.000{col 58}{space 4}-.4427876{col 71}{space 3}-.2996979
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.681129{col 30}{space 2} .1173188{col 41}{space 1}   39.90{col 50}{space 3}0.000{col 58}{space 4} 4.451188{col 71}{space 3} 4.911069
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80537389
         {txt}sigma_e {c |} {res} 1.2203555
             {txt}rho {c |} {res} .30339527{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0145                                         {txt}min = {res}         1
{txt}     between = {res}0.2217                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1643                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1586.39
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0696607{col 30}{space 2} .0204695{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0295411{col 71}{space 3} .1097802
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0460001{col 30}{space 2} .0074877{col 41}{space 1}   -6.14{col 50}{space 3}0.000{col 58}{space 4}-.0606758{col 71}{space 3}-.0313244
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0048112{col 30}{space 2} .0054391{col 41}{space 1}   -0.88{col 50}{space 3}0.376{col 58}{space 4}-.0154716{col 71}{space 3} .0058493
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0241646{col 30}{space 2} .0690823{col 41}{space 1}   -0.35{col 50}{space 3}0.726{col 58}{space 4}-.1595634{col 71}{space 3} .1112343
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0008488{col 30}{space 2} .0011099{col 41}{space 1}   -0.76{col 50}{space 3}0.444{col 58}{space 4}-.0030241{col 71}{space 3} .0013265
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0125277{col 30}{space 2} .0397705{col 41}{space 1}    0.31{col 50}{space 3}0.753{col 58}{space 4} -.065421{col 71}{space 3} .0904764
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2605973{col 30}{space 2} .0364329{col 41}{space 1}    7.15{col 50}{space 3}0.000{col 58}{space 4} .1891902{col 71}{space 3} .3320044
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2311291{col 30}{space 2} .0915295{col 41}{space 1}    2.53{col 50}{space 3}0.012{col 58}{space 4} .0517345{col 71}{space 3} .4105236
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2841278{col 30}{space 2} .0498799{col 41}{space 1}    5.70{col 50}{space 3}0.000{col 58}{space 4}  .186365{col 71}{space 3} .3818906
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0528112{col 30}{space 2} .0590252{col 41}{space 1}    0.89{col 50}{space 3}0.371{col 58}{space 4} -.062876{col 71}{space 3} .1684984
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1448057{col 30}{space 2} .0398637{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4} .0666743{col 71}{space 3} .2229372
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2155919{col 30}{space 2} .0421585{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4} .1329627{col 71}{space 3} .2982211
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1477797{col 30}{space 2} .0353462{col 41}{space 1}   -4.18{col 50}{space 3}0.000{col 58}{space 4}-.2170571{col 71}{space 3}-.0785024
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0032611{col 30}{space 2} .0030605{col 41}{space 1}    1.07{col 50}{space 3}0.287{col 58}{space 4}-.0027374{col 71}{space 3} .0092596
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1225947{col 30}{space 2} .0327056{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4}  .058493{col 71}{space 3} .1866965
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3100883{col 30}{space 2} .1217745{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} .0714146{col 71}{space 3}  .548762
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4186163{col 30}{space 2} .0685851{col 41}{space 1}    6.10{col 50}{space 3}0.000{col 58}{space 4} .2841919{col 71}{space 3} .5530407
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4776078{col 30}{space 2}  .079866{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .3210733{col 71}{space 3} .6341423
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} -.052829{col 30}{space 2}  .057986{col 41}{space 1}   -0.91{col 50}{space 3}0.362{col 58}{space 4}-.1664796{col 71}{space 3} .0608215
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2742097{col 30}{space 2} .0600938{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1564279{col 71}{space 3} .3919914
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0273091{col 30}{space 2} .0250265{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4}-.0763603{col 71}{space 3}  .021742
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0137858{col 30}{space 2} .0388495{col 41}{space 1}   -0.35{col 50}{space 3}0.723{col 58}{space 4}-.0899294{col 71}{space 3} .0623578
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0238106{col 30}{space 2} .0334902{col 41}{space 1}    0.71{col 50}{space 3}0.477{col 58}{space 4} -.041829{col 71}{space 3} .0894503
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0711894{col 30}{space 2} .0395905{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0064066{col 71}{space 3} .1487854
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.693077{col 30}{space 2} .1174128{col 41}{space 1}   39.97{col 50}{space 3}0.000{col 58}{space 4} 4.462952{col 71}{space 3} 4.923201
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .74824362
         {txt}sigma_e {c |} {res} 1.2113538
             {txt}rho {c |} {res}  .2761719{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0425                                         {txt}min = {res}         1
{txt}     between = {res}0.2939                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1885                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2258.38
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0278767{col 30}{space 2} .0140393{col 41}{space 1}    1.99{col 50}{space 3}0.047{col 58}{space 4} .0003602{col 71}{space 3} .0553932
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0332847{col 30}{space 2} .0048451{col 41}{space 1}   -6.87{col 50}{space 3}0.000{col 58}{space 4}-.0427808{col 71}{space 3}-.0237885
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0176799{col 30}{space 2} .0056036{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4}  .006697{col 71}{space 3} .0286628
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0231773{col 30}{space 2} .0623045{col 41}{space 1}   -0.37{col 50}{space 3}0.710{col 58}{space 4}-.1452918{col 71}{space 3} .0989373
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0002608{col 30}{space 2} .0010581{col 41}{space 1}   -0.25{col 50}{space 3}0.805{col 58}{space 4}-.0023346{col 71}{space 3}  .001813
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0399883{col 30}{space 2} .0353135{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4} -.029225{col 71}{space 3} .1092015
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3427725{col 30}{space 2} .0349516{col 41}{space 1}    9.81{col 50}{space 3}0.000{col 58}{space 4} .2742687{col 71}{space 3} .4112763
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2191987{col 30}{space 2} .0573801{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .1067357{col 71}{space 3} .3316616
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .239045{col 30}{space 2} .0384033{col 41}{space 1}    6.22{col 50}{space 3}0.000{col 58}{space 4} .1637759{col 71}{space 3} .3143141
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3575045{col 30}{space 2} .0386337{col 41}{space 1}    9.25{col 50}{space 3}0.000{col 58}{space 4} .2817838{col 71}{space 3} .4332252
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0378401{col 30}{space 2} .0312196{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0233493{col 71}{space 3} .0990294
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1998943{col 30}{space 2}  .032964{col 41}{space 1}    6.06{col 50}{space 3}0.000{col 58}{space 4} .1352862{col 71}{space 3} .2645025
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0080177{col 30}{space 2} .0253549{col 41}{space 1}    0.32{col 50}{space 3}0.752{col 58}{space 4}-.0416771{col 71}{space 3} .0577124
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0017957{col 30}{space 2} .0017565{col 41}{space 1}    1.02{col 50}{space 3}0.307{col 58}{space 4} -.001647{col 71}{space 3} .0052385
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0327418{col 30}{space 2} .0279449{col 41}{space 1}    1.17{col 50}{space 3}0.241{col 58}{space 4}-.0220292{col 71}{space 3} .0875129
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1553336{col 30}{space 2} .0888374{col 41}{space 1}    1.75{col 50}{space 3}0.080{col 58}{space 4}-.0187844{col 71}{space 3} .3294517
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3557282{col 30}{space 2} .0638678{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .2305497{col 71}{space 3} .4809068
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .246147{col 30}{space 2}   .07203{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .1049708{col 71}{space 3} .3873232
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1202511{col 30}{space 2}  .057297{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4}  .007951{col 71}{space 3} .2325511
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2730749{col 30}{space 2} .0555177{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .1642622{col 71}{space 3} .3818875
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .2115323{col 30}{space 2} .0236576{col 41}{space 1}    8.94{col 50}{space 3}0.000{col 58}{space 4} .1651642{col 71}{space 3} .2579004
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1353429{col 30}{space 2} .0403319{col 41}{space 1}   -3.36{col 50}{space 3}0.001{col 58}{space 4} -.214392{col 71}{space 3}-.0562938
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} -.055914{col 30}{space 2} .0357476{col 41}{space 1}   -1.56{col 50}{space 3}0.118{col 58}{space 4} -.125978{col 71}{space 3} .0141501
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3580385{col 30}{space 2} .0356386{col 41}{space 1}   10.05{col 50}{space 3}0.000{col 58}{space 4}  .288188{col 71}{space 3} .4278889
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1085814{col 30}{space 2} .0355047{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0389935{col 71}{space 3} .1781694
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2995175{col 30}{space 2} .0325429{col 41}{space 1}    9.20{col 50}{space 3}0.000{col 58}{space 4} .2357346{col 71}{space 3} .3633004
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.177554{col 30}{space 2} .1387171{col 41}{space 1}   22.91{col 50}{space 3}0.000{col 58}{space 4} 2.905674{col 71}{space 3} 3.449435
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75374506
         {txt}sigma_e {c |} {res} 1.2493559
             {txt}rho {c |} {res} .26685101{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S16_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill _cons)
{res}{txt}(note: file S16_farmer.rtf not found)
(output written to {browse  `"S16_farmer.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. *                          town_village_level                                  *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0234                                         {txt}min = {res}         1
{txt}     between = {res}0.3597                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2735                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 16994.82
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0266521{col 30}{space 2} .0081516{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0106752{col 71}{space 3} .0426291
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0020965{col 30}{space 2}  .000232{col 41}{space 1}   -9.04{col 50}{space 3}0.000{col 58}{space 4}-.0025511{col 71}{space 3}-.0016418
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0011868{col 30}{space 2} .0025658{col 41}{space 1}   -0.46{col 50}{space 3}0.644{col 58}{space 4}-.0062156{col 71}{space 3}  .003842
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .003926{col 30}{space 2}  .029926{col 41}{space 1}    0.13{col 50}{space 3}0.896{col 58}{space 4} -.054728{col 71}{space 3}   .06258
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0010543{col 30}{space 2} .0004923{col 41}{space 1}    2.14{col 50}{space 3}0.032{col 58}{space 4} .0000893{col 71}{space 3} .0020193
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0319447{col 30}{space 2} .0182341{col 41}{space 1}    1.75{col 50}{space 3}0.080{col 58}{space 4}-.0037935{col 71}{space 3}  .067683
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2960028{col 30}{space 2} .0155146{col 41}{space 1}   19.08{col 50}{space 3}0.000{col 58}{space 4} .2655947{col 71}{space 3} .3264109
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1070672{col 30}{space 2} .0318297{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4} .0446821{col 71}{space 3} .1694522
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1713861{col 30}{space 2} .0201032{col 41}{space 1}    8.53{col 50}{space 3}0.000{col 58}{space 4} .1319846{col 71}{space 3} .2107876
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1585647{col 30}{space 2} .0243952{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4}  .110751{col 71}{space 3} .2063784
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1345803{col 30}{space 2} .0211572{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .0931129{col 71}{space 3} .1760478
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2073081{col 30}{space 2} .0192983{col 41}{space 1}   10.74{col 50}{space 3}0.000{col 58}{space 4}  .169484{col 71}{space 3} .2451321
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0478669{col 30}{space 2} .0146352{col 41}{space 1}   -3.27{col 50}{space 3}0.001{col 58}{space 4}-.0765513{col 71}{space 3}-.0191824
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005521{col 30}{space 2} .0011065{col 41}{space 1}    0.50{col 50}{space 3}0.618{col 58}{space 4}-.0016165{col 71}{space 3} .0027208
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1452414{col 30}{space 2}  .016275{col 41}{space 1}    8.92{col 50}{space 3}0.000{col 58}{space 4} .1133429{col 71}{space 3} .1771398
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0736034{col 30}{space 2} .0426065{col 41}{space 1}    1.73{col 50}{space 3}0.084{col 58}{space 4}-.0099038{col 71}{space 3} .1571106
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5323465{col 30}{space 2} .0293633{col 41}{space 1}   18.13{col 50}{space 3}0.000{col 58}{space 4} .4747955{col 71}{space 3} .5898975
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6334047{col 30}{space 2} .0331506{col 41}{space 1}   19.11{col 50}{space 3}0.000{col 58}{space 4} .5684307{col 71}{space 3} .6983787
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1238541{col 30}{space 2} .0318894{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0613522{col 71}{space 3} .1863561
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1654069{col 30}{space 2} .0270892{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4}  .112313{col 71}{space 3} .2185008
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1098939{col 30}{space 2} .0105766{col 41}{space 1}   10.39{col 50}{space 3}0.000{col 58}{space 4} .0891641{col 71}{space 3} .1306237
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3236911{col 30}{space 2} .0379745{col 41}{space 1}   -8.52{col 50}{space 3}0.000{col 58}{space 4}-.3981199{col 71}{space 3}-.2492624
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2} -1.58129{col 30}{space 2} .0367965{col 41}{space 1}  -42.97{col 50}{space 3}0.000{col 58}{space 4} -1.65341{col 71}{space 3} -1.50917
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5004951{col 30}{space 2} .0371076{col 41}{space 1}  -13.49{col 50}{space 3}0.000{col 58}{space 4}-.5732247{col 71}{space 3}-.4277655
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3157445{col 30}{space 2} .0374705{col 41}{space 1}   -8.43{col 50}{space 3}0.000{col 58}{space 4}-.3891853{col 71}{space 3}-.2423038
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3057794{col 30}{space 2} .0470982{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .2134687{col 71}{space 3} .3980901
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2391618{col 30}{space 2} .0477016{col 41}{space 1}   -5.01{col 50}{space 3}0.000{col 58}{space 4}-.3326552{col 71}{space 3}-.1456684
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0176848{col 30}{space 2} .0360596{col 41}{space 1}    0.49{col 50}{space 3}0.624{col 58}{space 4}-.0529907{col 71}{space 3} .0883603
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0354299{col 30}{space 2} .0404707{col 41}{space 1}    0.88{col 50}{space 3}0.381{col 58}{space 4}-.0438912{col 71}{space 3} .1147511
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0063838{col 30}{space 2} .0367258{col 41}{space 1}    0.17{col 50}{space 3}0.862{col 58}{space 4}-.0655974{col 71}{space 3} .0783651
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1101772{col 30}{space 2} .0407836{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0302428{col 71}{space 3} .1901116
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1161746{col 30}{space 2} .0415063{col 41}{space 1}   -2.80{col 50}{space 3}0.005{col 58}{space 4}-.1975255{col 71}{space 3}-.0348236
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1657327{col 30}{space 2} .0395838{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .0881499{col 71}{space 3} .2433154
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2152886{col 30}{space 2} .0612359{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}-.3353089{col 71}{space 3}-.0952684
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4127358{col 30}{space 2} .0414824{col 41}{space 1}    9.95{col 50}{space 3}0.000{col 58}{space 4} .3314318{col 71}{space 3} .4940397
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0058133{col 30}{space 2} .0405089{col 41}{space 1}   -0.14{col 50}{space 3}0.886{col 58}{space 4}-.0852093{col 71}{space 3} .0735827
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 3.979231{col 30}{space 2} .0674752{col 41}{space 1}   58.97{col 50}{space 3}0.000{col 58}{space 4} 3.846982{col 71}{space 3}  4.11148
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78586217
         {txt}sigma_e {c |} {res} 1.2264056
             {txt}rho {c |} {res} .29108444{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0201                                         {txt}min = {res}         1
{txt}     between = {res}0.3142                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2044                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1912.85
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0581107{col 30}{space 2} .0174618{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0238862{col 71}{space 3} .0923351
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0059293{col 30}{space 2} .0006357{col 41}{space 1}   -9.33{col 50}{space 3}0.000{col 58}{space 4}-.0071753{col 71}{space 3}-.0046834
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0506798{col 30}{space 2} .0074881{col 41}{space 1}    6.77{col 50}{space 3}0.000{col 58}{space 4} .0360033{col 71}{space 3} .0653562
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0298704{col 30}{space 2} .0621653{col 41}{space 1}   -0.48{col 50}{space 3}0.631{col 58}{space 4}-.1517121{col 71}{space 3} .0919713
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023231{col 30}{space 2} .0010527{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.0043863{col 71}{space 3}-.0002599
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0476141{col 30}{space 2} .0386709{col 41}{space 1}   -1.23{col 50}{space 3}0.218{col 58}{space 4}-.1234077{col 71}{space 3} .0281794
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3171178{col 30}{space 2} .0322744{col 41}{space 1}    9.83{col 50}{space 3}0.000{col 58}{space 4}  .253861{col 71}{space 3} .3803745
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2111582{col 30}{space 2} .1619108{col 41}{space 1}   -1.30{col 50}{space 3}0.192{col 58}{space 4}-.5284975{col 71}{space 3} .1061811
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1729045{col 30}{space 2} .0381051{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .0982198{col 71}{space 3} .2475892
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1582525{col 30}{space 2} .0476942{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0647735{col 71}{space 3} .2517315
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1069691{col 30}{space 2} .0715288{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0332248{col 71}{space 3} .2471629
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2017771{col 30}{space 2} .0523875{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0990994{col 71}{space 3} .3044547
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1248735{col 30}{space 2} .0301373{col 41}{space 1}   -4.14{col 50}{space 3}0.000{col 58}{space 4}-.1839415{col 71}{space 3}-.0658055
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0134438{col 30}{space 2} .0037535{col 41}{space 1}    3.58{col 50}{space 3}0.000{col 58}{space 4} .0060872{col 71}{space 3} .0208005
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2614093{col 30}{space 2} .0317985{col 41}{space 1}    8.22{col 50}{space 3}0.000{col 58}{space 4} .1990854{col 71}{space 3} .3237332
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .823321{col 30}{space 2} .2735278{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .2872164{col 71}{space 3} 1.359426
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4309945{col 30}{space 2} .0590719{col 41}{space 1}    7.30{col 50}{space 3}0.000{col 58}{space 4} .3152158{col 71}{space 3} .5467733
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4407901{col 30}{space 2}  .071085{col 41}{space 1}    6.20{col 50}{space 3}0.000{col 58}{space 4}  .301466{col 71}{space 3} .5801141
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3202007{col 30}{space 2}  .115141{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0945286{col 71}{space 3} .5458729
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .140379{col 30}{space 2} .0669277{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0092031{col 71}{space 3} .2715549
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0756867{col 30}{space 2} .0215821{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0333866{col 71}{space 3} .1179868
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1572157{col 30}{space 2} .0229872{col 41}{space 1}   -6.84{col 50}{space 3}0.000{col 58}{space 4}-.2022698{col 71}{space 3}-.1121615
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.594025{col 30}{space 2} .1076352{col 41}{space 1}   24.10{col 50}{space 3}0.000{col 58}{space 4} 2.383064{col 71}{space 3} 2.804986
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69844831
         {txt}sigma_e {c |} {res}  1.056077
             {txt}rho {c |} {res} .30429875{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0203                                         {txt}min = {res}         1
{txt}     between = {res}0.3873                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2473                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1232.94
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0202957{col 30}{space 2} .0291997{col 41}{space 1}    0.70{col 50}{space 3}0.487{col 58}{space 4}-.0369347{col 71}{space 3} .0775261
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.015361{col 30}{space 2} .0037215{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4} -.022655{col 71}{space 3} -.008067
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0018681{col 30}{space 2} .0118309{col 41}{space 1}   -0.16{col 50}{space 3}0.875{col 58}{space 4}-.0250563{col 71}{space 3} .0213201
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1877951{col 30}{space 2} .1129522{col 41}{space 1}   -1.66{col 50}{space 3}0.096{col 58}{space 4}-.4091774{col 71}{space 3} .0335872
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0015993{col 30}{space 2} .0017951{col 41}{space 1}   -0.89{col 50}{space 3}0.373{col 58}{space 4}-.0051177{col 71}{space 3} .0019191
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0990529{col 30}{space 2} .0635887{col 41}{space 1}   -1.56{col 50}{space 3}0.119{col 58}{space 4}-.2236845{col 71}{space 3} .0255787
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3158726{col 30}{space 2} .0609119{col 41}{space 1}    5.19{col 50}{space 3}0.000{col 58}{space 4} .1964874{col 71}{space 3} .4352578
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3135929{col 30}{space 2} .2131479{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.1041694{col 71}{space 3} .7313552
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1266319{col 30}{space 2} .0722968{col 41}{space 1}    1.75{col 50}{space 3}0.080{col 58}{space 4}-.0150672{col 71}{space 3}  .268331
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2177018{col 30}{space 2} .1677111{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4} -.111006{col 71}{space 3} .5464096
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1180909{col 30}{space 2} .0877347{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4}-.0538659{col 71}{space 3} .2900477
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2432057{col 30}{space 2} .0606133{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .1244058{col 71}{space 3} .3620056
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1563478{col 30}{space 2} .0450584{col 41}{space 1}   -3.47{col 50}{space 3}0.001{col 58}{space 4}-.2446606{col 71}{space 3}-.0680349
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0841687{col 30}{space 2} .0347604{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0160396{col 71}{space 3} .1522978
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0928088{col 30}{space 2}  .062384{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0294616{col 71}{space 3} .2150792
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1489895{col 30}{space 2} .3278108{col 41}{space 1}    0.45{col 50}{space 3}0.649{col 58}{space 4}-.4935078{col 71}{space 3} .7914868
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6754619{col 30}{space 2} .1159616{col 41}{space 1}    5.82{col 50}{space 3}0.000{col 58}{space 4} .4481813{col 71}{space 3} .9027424
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7933011{col 30}{space 2} .2154096{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .3711061{col 71}{space 3} 1.215496
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4008193{col 30}{space 2} .1293016{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .1473928{col 71}{space 3} .6542457
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3405147{col 30}{space 2} .1091772{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .1265314{col 71}{space 3}  .554498
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0276523{col 30}{space 2}  .045692{col 41}{space 1}   -0.61{col 50}{space 3}0.545{col 58}{space 4} -.117207{col 71}{space 3} .0619024
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2754323{col 30}{space 2} .0601959{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .1574504{col 71}{space 3} .3934141
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .119606{col 30}{space 2} .0529796{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0157679{col 71}{space 3}  .223444
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.314561{col 30}{space 2} .2665458{col 41}{space 1}   19.94{col 50}{space 3}0.000{col 58}{space 4} 4.792141{col 71}{space 3} 5.836981
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72718942
         {txt}sigma_e {c |} {res} 1.2979102
             {txt}rho {c |} {res} .23891313{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0367                                         {txt}min = {res}         1
{txt}     between = {res}0.1776                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1333                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   904.03
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .1133301{col 30}{space 2}  .039134{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0366289{col 71}{space 3} .1900314
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0017301{col 30}{space 2} .0003419{col 41}{space 1}   -5.06{col 50}{space 3}0.000{col 58}{space 4}-.0024002{col 71}{space 3}  -.00106
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0111906{col 30}{space 2} .0071314{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0027867{col 71}{space 3} .0251679
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0948494{col 30}{space 2} .1151754{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.3205891{col 71}{space 3} .1308903
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0037003{col 30}{space 2} .0015499{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0006626{col 71}{space 3}  .006738
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0632067{col 30}{space 2}  .067945{col 41}{space 1}    0.93{col 50}{space 3}0.352{col 58}{space 4}-.0699631{col 71}{space 3} .1963765
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3072215{col 30}{space 2} .0517216{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4}  .205849{col 71}{space 3} .4085939
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4498381{col 30}{space 2} .1462229{col 41}{space 1}    3.08{col 50}{space 3}0.002{col 58}{space 4} .1632465{col 71}{space 3} .7364296
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0798156{col 30}{space 2} .0862336{col 41}{space 1}    0.93{col 50}{space 3}0.355{col 58}{space 4}-.0891991{col 71}{space 3} .2488303
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .159833{col 30}{space 2} .1821609{col 41}{space 1}    0.88{col 50}{space 3}0.380{col 58}{space 4}-.1971959{col 71}{space 3} .5168618
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2795717{col 30}{space 2} .1088771{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .0661766{col 71}{space 3} .4929669
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2114249{col 30}{space 2} .0782606{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4}-.3648129{col 71}{space 3}-.0580368
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1227279{col 30}{space 2} .0461284{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4}-.2131378{col 71}{space 3}-.0323179
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012179{col 30}{space 2} .0015367{col 41}{space 1}   -0.79{col 50}{space 3}0.428{col 58}{space 4}-.0042298{col 71}{space 3}  .001794
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2367433{col 30}{space 2} .2149033{col 41}{space 1}    1.10{col 50}{space 3}0.271{col 58}{space 4}-.1844594{col 71}{space 3} .6579461
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0537411{col 30}{space 2} .1739453{col 41}{space 1}   -0.31{col 50}{space 3}0.757{col 58}{space 4}-.3946677{col 71}{space 3} .2871854
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2627171{col 30}{space 2} .1044822{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0579358{col 71}{space 3} .4674984
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7107679{col 30}{space 2} .1964091{col 41}{space 1}    3.62{col 50}{space 3}0.000{col 58}{space 4} .3258132{col 71}{space 3} 1.095723
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0063399{col 30}{space 2} .1347278{col 41}{space 1}   -0.05{col 50}{space 3}0.962{col 58}{space 4}-.2704015{col 71}{space 3} .2577217
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4559935{col 30}{space 2} .0952961{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4} .2692165{col 71}{space 3} .6427705
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0430822{col 30}{space 2} .0459612{col 41}{space 1}    0.94{col 50}{space 3}0.349{col 58}{space 4}-.0470001{col 71}{space 3} .1331645
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2662287{col 30}{space 2} .0444706{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .1790678{col 71}{space 3} .3533895
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  3.75763{col 30}{space 2} .1616355{col 41}{space 1}   23.25{col 50}{space 3}0.000{col 58}{space 4}  3.44083{col 71}{space 3}  4.07443
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50990022
         {txt}sigma_e {c |} {res} 1.4274758
             {txt}rho {c |} {res} .11315658{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0356                                         {txt}min = {res}         1
{txt}     between = {res}0.3127                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2656                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3761.74
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .055891{col 30}{space 2} .0176367{col 41}{space 1}    3.17{col 50}{space 3}0.002{col 58}{space 4} .0213237{col 71}{space 3} .0904584
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0186904{col 30}{space 2} .0026728{col 41}{space 1}   -6.99{col 50}{space 3}0.000{col 58}{space 4} -.023929{col 71}{space 3}-.0134518
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0256947{col 30}{space 2} .0049207{col 41}{space 1}   -5.22{col 50}{space 3}0.000{col 58}{space 4}-.0353391{col 71}{space 3}-.0160503
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1748944{col 30}{space 2} .0590872{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0590856{col 71}{space 3} .2907031
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0045946{col 30}{space 2} .0010348{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .0025664{col 71}{space 3} .0066228
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2942286{col 30}{space 2} .0429803{col 41}{space 1}    6.85{col 50}{space 3}0.000{col 58}{space 4} .2099888{col 71}{space 3} .3784683
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1885568{col 30}{space 2}  .029709{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .1303282{col 71}{space 3} .2467855
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0180582{col 30}{space 2} .0457627{col 41}{space 1}   -0.39{col 50}{space 3}0.693{col 58}{space 4}-.1077514{col 71}{space 3}  .071635
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1502506{col 30}{space 2} .0438844{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0642389{col 71}{space 3} .2362624
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0620426{col 30}{space 2} .0566865{col 41}{space 1}    1.09{col 50}{space 3}0.274{col 58}{space 4}-.0490608{col 71}{space 3} .1731461
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2394593{col 30}{space 2} .0673357{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .1074837{col 71}{space 3} .3714349
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3100744{col 30}{space 2} .0472818{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .2174037{col 71}{space 3} .4027451
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0739316{col 30}{space 2} .0481634{col 41}{space 1}    1.54{col 50}{space 3}0.125{col 58}{space 4}-.0204669{col 71}{space 3} .1683301
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0045302{col 30}{space 2}  .005942{col 41}{space 1}   -0.76{col 50}{space 3}0.446{col 58}{space 4}-.0161764{col 71}{space 3}  .007116
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3286412{col 30}{space 2} .0609468{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .2091877{col 71}{space 3} .4480948
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1167421{col 30}{space 2} .0603802{col 41}{space 1}    1.93{col 50}{space 3}0.053{col 58}{space 4}-.0016009{col 71}{space 3} .2350851
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .706666{col 30}{space 2} .0634535{col 41}{space 1}   11.14{col 50}{space 3}0.000{col 58}{space 4} .5822993{col 71}{space 3} .8310326
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8052066{col 30}{space 2} .0679033{col 41}{space 1}   11.86{col 50}{space 3}0.000{col 58}{space 4} .6721186{col 71}{space 3} .9382946
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1408477{col 30}{space 2} .0849849{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4}-.0257196{col 71}{space 3}  .307415
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0390911{col 30}{space 2}  .059179{col 41}{space 1}   -0.66{col 50}{space 3}0.509{col 58}{space 4}-.1550798{col 71}{space 3} .0768976
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1469333{col 30}{space 2} .0222992{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4} .1032277{col 71}{space 3} .1906388
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5260478{col 30}{space 2} .0368514{col 41}{space 1}  -14.27{col 50}{space 3}0.000{col 58}{space 4}-.5982752{col 71}{space 3}-.4538203
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5096361{col 30}{space 2} .0375856{col 41}{space 1}  -13.56{col 50}{space 3}0.000{col 58}{space 4}-.5833024{col 71}{space 3}-.4359698
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3589674{col 30}{space 2} .0377135{col 41}{space 1}   -9.52{col 50}{space 3}0.000{col 58}{space 4}-.4328846{col 71}{space 3}-.2850502
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.853609{col 30}{space 2} .1014578{col 41}{space 1}   37.98{col 50}{space 3}0.000{col 58}{space 4} 3.654756{col 71}{space 3} 4.052463
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .8228866
         {txt}sigma_e {c |} {res} 1.2204851
             {txt}rho {c |} {res} .31251866{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0121                                         {txt}min = {res}         1
{txt}     between = {res}0.2180                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1616                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1548.75
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .013283{col 30}{space 2} .0227427{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0312918{col 71}{space 3} .0578579
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0135419{col 30}{space 2} .0048185{col 41}{space 1}   -2.81{col 50}{space 3}0.005{col 58}{space 4}-.0229861{col 71}{space 3}-.0040978
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0041656{col 30}{space 2}  .005436{col 41}{space 1}   -0.77{col 50}{space 3}0.444{col 58}{space 4}  -.01482{col 71}{space 3} .0064889
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0238986{col 30}{space 2} .0690799{col 41}{space 1}   -0.35{col 50}{space 3}0.729{col 58}{space 4}-.1592928{col 71}{space 3} .1114956
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0007266{col 30}{space 2} .0011093{col 41}{space 1}   -0.65{col 50}{space 3}0.512{col 58}{space 4}-.0029007{col 71}{space 3} .0014476
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .009771{col 30}{space 2} .0398965{col 41}{space 1}    0.24{col 50}{space 3}0.807{col 58}{space 4}-.0684248{col 71}{space 3} .0879667
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2651445{col 30}{space 2} .0364433{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .1937171{col 71}{space 3}  .336572
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2201246{col 30}{space 2} .0916752{col 41}{space 1}    2.40{col 50}{space 3}0.016{col 58}{space 4} .0404445{col 71}{space 3} .3998047
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2825757{col 30}{space 2}   .04996{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4}  .184656{col 71}{space 3} .3804955
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0268065{col 30}{space 2}  .058986{col 41}{space 1}    0.45{col 50}{space 3}0.650{col 58}{space 4} -.088804{col 71}{space 3}  .142417
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1515624{col 30}{space 2} .0399515{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .0732589{col 71}{space 3} .2298659
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2214132{col 30}{space 2} .0422338{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .1386364{col 71}{space 3}   .30419
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1545356{col 30}{space 2} .0353342{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4}-.2237894{col 71}{space 3}-.0852818
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0041361{col 30}{space 2} .0030564{col 41}{space 1}    1.35{col 50}{space 3}0.176{col 58}{space 4}-.0018544{col 71}{space 3} .0101265
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1406121{col 30}{space 2} .0329059{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0761177{col 71}{space 3} .2051065
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3285887{col 30}{space 2} .1223584{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0887706{col 71}{space 3} .5684068
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4109809{col 30}{space 2} .0687277{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .2762771{col 71}{space 3} .5456847
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4704916{col 30}{space 2} .0803393{col 41}{space 1}    5.86{col 50}{space 3}0.000{col 58}{space 4} .3130294{col 71}{space 3} .6279538
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0522335{col 30}{space 2} .0581345{col 41}{space 1}   -0.90{col 50}{space 3}0.369{col 58}{space 4} -.166175{col 71}{space 3}  .061708
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2829832{col 30}{space 2}   .06024{col 41}{space 1}    4.70{col 50}{space 3}0.000{col 58}{space 4} .1649149{col 71}{space 3} .4010514
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0014806{col 30}{space 2} .0274933{col 41}{space 1}    0.05{col 50}{space 3}0.957{col 58}{space 4}-.0524054{col 71}{space 3} .0553666
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0142773{col 30}{space 2} .0387492{col 41}{space 1}    0.37{col 50}{space 3}0.713{col 58}{space 4}-.0616698{col 71}{space 3} .0902243
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0472657{col 30}{space 2} .0342064{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.0197775{col 71}{space 3}  .114309
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0216761{col 30}{space 2} .0381228{col 41}{space 1}    0.57{col 50}{space 3}0.570{col 58}{space 4}-.0530433{col 71}{space 3} .0963955
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.692565{col 30}{space 2} .1271656{col 41}{space 1}   36.90{col 50}{space 3}0.000{col 58}{space 4} 4.443325{col 71}{space 3} 4.941805
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .74881967
         {txt}sigma_e {c |} {res} 1.2121707
             {txt}rho {c |} {res} .27621006{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0424                                         {txt}min = {res}         1
{txt}     between = {res}0.2941                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1891                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2265.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0237094{col 30}{space 2} .0145786{col 41}{space 1}    1.63{col 50}{space 3}0.104{col 58}{space 4}-.0048643{col 71}{space 3}  .052283
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0182467{col 30}{space 2} .0031917{col 41}{space 1}   -5.72{col 50}{space 3}0.000{col 58}{space 4}-.0245022{col 71}{space 3}-.0119912
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0179878{col 30}{space 2}  .005613{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4} .0069866{col 71}{space 3} .0289891
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0293961{col 30}{space 2} .0622764{col 41}{space 1}   -0.47{col 50}{space 3}0.637{col 58}{space 4}-.1514556{col 71}{space 3} .0926634
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000328{col 30}{space 2} .0010553{col 41}{space 1}    0.03{col 50}{space 3}0.975{col 58}{space 4}-.0020356{col 71}{space 3} .0021012
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0402123{col 30}{space 2} .0352891{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4} -.028953{col 71}{space 3} .1093777
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3399926{col 30}{space 2} .0350562{col 41}{space 1}    9.70{col 50}{space 3}0.000{col 58}{space 4} .2712837{col 71}{space 3} .4087015
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2213746{col 30}{space 2} .0575504{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .1085778{col 71}{space 3} .3341713
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2413617{col 30}{space 2} .0383766{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4}  .166145{col 71}{space 3} .3165784
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3619463{col 30}{space 2} .0386622{col 41}{space 1}    9.36{col 50}{space 3}0.000{col 58}{space 4} .2861698{col 71}{space 3} .4377228
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0357883{col 30}{space 2} .0312194{col 41}{space 1}    1.15{col 50}{space 3}0.252{col 58}{space 4}-.0254005{col 71}{space 3} .0969771
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1980333{col 30}{space 2} .0329926{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .1333689{col 71}{space 3} .2626976
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0052832{col 30}{space 2} .0253977{col 41}{space 1}    0.21{col 50}{space 3}0.835{col 58}{space 4}-.0444954{col 71}{space 3} .0550619
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0017528{col 30}{space 2} .0017419{col 41}{space 1}    1.01{col 50}{space 3}0.314{col 58}{space 4}-.0016613{col 71}{space 3}  .005167
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0302339{col 30}{space 2} .0279309{col 41}{space 1}    1.08{col 50}{space 3}0.279{col 58}{space 4}-.0245096{col 71}{space 3} .0849774
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1576713{col 30}{space 2} .0886146{col 41}{space 1}    1.78{col 50}{space 3}0.075{col 58}{space 4}  -.01601{col 71}{space 3} .3313527
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3526953{col 30}{space 2}  .063779{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .2276907{col 71}{space 3} .4776998
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2454286{col 30}{space 2} .0721895{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .1039397{col 71}{space 3} .3869175
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1266562{col 30}{space 2}   .05731{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0143307{col 71}{space 3} .2389818
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .282311{col 30}{space 2} .0555768{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1733825{col 71}{space 3} .3912396
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .2286493{col 30}{space 2} .0243826{col 41}{space 1}    9.38{col 50}{space 3}0.000{col 58}{space 4} .1808603{col 71}{space 3} .2764384
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1464174{col 30}{space 2} .0401485{col 41}{space 1}   -3.65{col 50}{space 3}0.000{col 58}{space 4}-.2251069{col 71}{space 3}-.0677278
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0666589{col 30}{space 2} .0356793{col 41}{space 1}   -1.87{col 50}{space 3}0.062{col 58}{space 4}-.1365891{col 71}{space 3} .0032713
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3602862{col 30}{space 2}  .035715{col 41}{space 1}   10.09{col 50}{space 3}0.000{col 58}{space 4}  .290286{col 71}{space 3} .4302864
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1107076{col 30}{space 2} .0357334{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .0406713{col 71}{space 3} .1807438
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2954491{col 30}{space 2} .0326023{col 41}{space 1}    9.06{col 50}{space 3}0.000{col 58}{space 4} .2315499{col 71}{space 3} .3593484
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.948834{col 30}{space 2} .1422552{col 41}{space 1}   20.73{col 50}{space 3}0.000{col 58}{space 4} 2.670019{col 71}{space 3} 3.227649
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75483156
         {txt}sigma_e {c |} {res} 1.2495169
             {txt}rho {c |} {res} .26736452{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S17_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town _cons)
{res}{txt}(note: file S17_farmer.rtf not found)
(output written to {browse  `"S17_farmer.rtf"'})

{com}. 
. 
. 
. 
. *                          dist_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0232                                         {txt}min = {res}         1
{txt}     between = {res}0.3553                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2695                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 16584.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0280259{col 30}{space 2} .0096009{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0092085{col 71}{space 3} .0468433
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0015615{col 30}{space 2}  .000193{col 41}{space 1}   -8.09{col 50}{space 3}0.000{col 58}{space 4}-.0019396{col 71}{space 3}-.0011833
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0018093{col 30}{space 2} .0025765{col 41}{space 1}   -0.70{col 50}{space 3}0.483{col 58}{space 4}-.0068592{col 71}{space 3} .0032406
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0079794{col 30}{space 2}  .029998{col 41}{space 1}    0.27{col 50}{space 3}0.790{col 58}{space 4}-.0508156{col 71}{space 3} .0667744
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0013444{col 30}{space 2}  .000495{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0003742{col 71}{space 3} .0023146
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0357235{col 30}{space 2} .0183002{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0001442{col 71}{space 3} .0715912
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2988637{col 30}{space 2} .0155405{col 41}{space 1}   19.23{col 50}{space 3}0.000{col 58}{space 4} .2684049{col 71}{space 3} .3293225
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1054066{col 30}{space 2}  .031802{col 41}{space 1}    3.31{col 50}{space 3}0.001{col 58}{space 4} .0430758{col 71}{space 3} .1677374
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1712349{col 30}{space 2} .0201107{col 41}{space 1}    8.51{col 50}{space 3}0.000{col 58}{space 4} .1318186{col 71}{space 3} .2106512
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1584805{col 30}{space 2} .0243898{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .1106774{col 71}{space 3} .2062836
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1348649{col 30}{space 2} .0211714{col 41}{space 1}    6.37{col 50}{space 3}0.000{col 58}{space 4} .0933697{col 71}{space 3} .1763601
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2067884{col 30}{space 2} .0192975{col 41}{space 1}   10.72{col 50}{space 3}0.000{col 58}{space 4} .1689661{col 71}{space 3} .2446108
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0470784{col 30}{space 2} .0146582{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4} -.075808{col 71}{space 3}-.0183488
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0009059{col 30}{space 2} .0011062{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0012623{col 71}{space 3} .0030741
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1624003{col 30}{space 2} .0163147{col 41}{space 1}    9.95{col 50}{space 3}0.000{col 58}{space 4}  .130424{col 71}{space 3} .1943765
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0865077{col 30}{space 2} .0427395{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0027397{col 71}{space 3} .1702756
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5341156{col 30}{space 2} .0294322{col 41}{space 1}   18.15{col 50}{space 3}0.000{col 58}{space 4} .4764295{col 71}{space 3} .5918017
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6062678{col 30}{space 2} .0332063{col 41}{space 1}   18.26{col 50}{space 3}0.000{col 58}{space 4} .5411846{col 71}{space 3}  .671351
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1122694{col 30}{space 2} .0319525{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0496435{col 71}{space 3} .1748952
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1488965{col 30}{space 2} .0271863{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4} .0956124{col 71}{space 3} .2021806
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0940082{col 30}{space 2} .0127873{col 41}{space 1}    7.35{col 50}{space 3}0.000{col 58}{space 4} .0689455{col 71}{space 3} .1190709
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4259122{col 30}{space 2} .0361082{col 41}{space 1}  -11.80{col 50}{space 3}0.000{col 58}{space 4}-.4966831{col 71}{space 3}-.3551414
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2} -1.53789{col 30}{space 2} .0399652{col 41}{space 1}  -38.48{col 50}{space 3}0.000{col 58}{space 4} -1.61622{col 71}{space 3} -1.45956
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5313811{col 30}{space 2} .0395674{col 41}{space 1}  -13.43{col 50}{space 3}0.000{col 58}{space 4}-.6089318{col 71}{space 3}-.4538303
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3447286{col 30}{space 2} .0400127{col 41}{space 1}   -8.62{col 50}{space 3}0.000{col 58}{space 4} -.423152{col 71}{space 3}-.2663051
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3244603{col 30}{space 2} .0475936{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .2311785{col 71}{space 3} .4177422
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.239504{col 30}{space 2} .0476576{col 41}{space 1}   -5.03{col 50}{space 3}0.000{col 58}{space 4}-.3329111{col 71}{space 3}-.1460969
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0274582{col 30}{space 2} .0360456{col 41}{space 1}    0.76{col 50}{space 3}0.446{col 58}{space 4}-.0431898{col 71}{space 3} .0981062
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0515225{col 30}{space 2} .0404232{col 41}{space 1}    1.27{col 50}{space 3}0.202{col 58}{space 4}-.0277055{col 71}{space 3} .1307505
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0171265{col 30}{space 2} .0367388{col 41}{space 1}    0.47{col 50}{space 3}0.641{col 58}{space 4}-.0548803{col 71}{space 3} .0891333
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1249078{col 30}{space 2} .0407809{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0449786{col 71}{space 3} .2048369
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1067973{col 30}{space 2} .0413902{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-.1879205{col 71}{space 3}-.0256741
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1796175{col 30}{space 2}  .039537{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1021263{col 71}{space 3} .2571087
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2113478{col 30}{space 2} .0611808{col 41}{space 1}   -3.45{col 50}{space 3}0.001{col 58}{space 4}-.3312599{col 71}{space 3}-.0914357
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4280211{col 30}{space 2} .0417445{col 41}{space 1}   10.25{col 50}{space 3}0.000{col 58}{space 4} .3462034{col 71}{space 3} .5098388
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}  .005122{col 30}{space 2} .0404696{col 41}{space 1}    0.13{col 50}{space 3}0.899{col 58}{space 4}-.0741969{col 71}{space 3} .0844409
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 3.986822{col 30}{space 2} .0785804{col 41}{space 1}   50.74{col 50}{space 3}0.000{col 58}{space 4} 3.832808{col 71}{space 3} 4.140837
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79202309
         {txt}sigma_e {c |} {res} 1.2265676
             {txt}rho {c |} {res} .29426298{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0200                                         {txt}min = {res}         1
{txt}     between = {res}0.3125                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2035                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1894.16
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0638542{col 30}{space 2} .0177091{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .0291449{col 71}{space 3} .0985635
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0054758{col 30}{space 2} .0006404{col 41}{space 1}   -8.55{col 50}{space 3}0.000{col 58}{space 4}-.0067311{col 71}{space 3}-.0042206
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0507368{col 30}{space 2} .0074917{col 41}{space 1}    6.77{col 50}{space 3}0.000{col 58}{space 4} .0360535{col 71}{space 3} .0654202
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.024406{col 30}{space 2} .0622222{col 41}{space 1}   -0.39{col 50}{space 3}0.695{col 58}{space 4}-.1463593{col 71}{space 3} .0975474
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025268{col 30}{space 2} .0010555{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-.0045955{col 71}{space 3}-.0004581
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0481895{col 30}{space 2} .0386577{col 41}{space 1}   -1.25{col 50}{space 3}0.213{col 58}{space 4}-.1239573{col 71}{space 3} .0275783
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3184856{col 30}{space 2} .0322874{col 41}{space 1}    9.86{col 50}{space 3}0.000{col 58}{space 4} .2552033{col 71}{space 3} .3817678
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2141886{col 30}{space 2} .1622014{col 41}{space 1}   -1.32{col 50}{space 3}0.187{col 58}{space 4}-.5320976{col 71}{space 3} .1037204
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1732328{col 30}{space 2} .0380997{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0985588{col 71}{space 3} .2479068
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1579225{col 30}{space 2} .0477189{col 41}{space 1}    3.31{col 50}{space 3}0.001{col 58}{space 4} .0643951{col 71}{space 3} .2514499
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1064094{col 30}{space 2} .0715585{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0338427{col 71}{space 3} .2466616
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2011438{col 30}{space 2} .0523803{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0984803{col 71}{space 3} .3038073
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1267314{col 30}{space 2} .0301839{col 41}{space 1}   -4.20{col 50}{space 3}0.000{col 58}{space 4}-.1858907{col 71}{space 3}-.0675721
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0139151{col 30}{space 2} .0037863{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0064942{col 71}{space 3} .0213361
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2669995{col 30}{space 2} .0316558{col 41}{space 1}    8.43{col 50}{space 3}0.000{col 58}{space 4} .2049553{col 71}{space 3} .3290436
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .852118{col 30}{space 2} .2735652{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4}   .31594{col 71}{space 3} 1.388296
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4283178{col 30}{space 2} .0591228{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .3124392{col 71}{space 3} .5441963
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4120639{col 30}{space 2} .0710828{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .2727442{col 71}{space 3} .5513836
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3110987{col 30}{space 2} .1154517{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0848176{col 71}{space 3} .5373798
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1294969{col 30}{space 2} .0670649{col 41}{space 1}    1.93{col 50}{space 3}0.053{col 58}{space 4}-.0019478{col 71}{space 3} .2609417
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0674848{col 30}{space 2} .0219661{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4}  .024432{col 71}{space 3} .1105376
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1584258{col 30}{space 2} .0230226{col 41}{space 1}   -6.88{col 50}{space 3}0.000{col 58}{space 4}-.2035492{col 71}{space 3}-.1133024
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.612101{col 30}{space 2} .1092145{col 41}{space 1}   23.92{col 50}{space 3}0.000{col 58}{space 4} 2.398045{col 71}{space 3} 2.826158
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69996499
         {txt}sigma_e {c |} {res} 1.0559523
             {txt}rho {c |} {res} .30526801{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.3902                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2490                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1225.41
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0647207{col 30}{space 2} .0438541{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.1506731{col 71}{space 3} .0212317
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0044134{col 30}{space 2} .0011187{col 41}{space 1}   -3.95{col 50}{space 3}0.000{col 58}{space 4}-.0066059{col 71}{space 3}-.0022208
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0024774{col 30}{space 2} .0119114{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-.0258234{col 71}{space 3} .0208686
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1942454{col 30}{space 2} .1127908{col 41}{space 1}   -1.72{col 50}{space 3}0.085{col 58}{space 4}-.4153113{col 71}{space 3} .0268205
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0021097{col 30}{space 2} .0017975{col 41}{space 1}   -1.17{col 50}{space 3}0.241{col 58}{space 4}-.0056328{col 71}{space 3} .0014133
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1186072{col 30}{space 2} .0634741{col 41}{space 1}   -1.87{col 50}{space 3}0.062{col 58}{space 4}-.2430142{col 71}{space 3} .0057998
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2981708{col 30}{space 2} .0608817{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .1788448{col 71}{space 3} .4174969
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3175115{col 30}{space 2} .2123392{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0986657{col 71}{space 3} .7336887
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .130254{col 30}{space 2} .0722526{col 41}{space 1}    1.80{col 50}{space 3}0.071{col 58}{space 4}-.0113585{col 71}{space 3} .2718665
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2332781{col 30}{space 2} .1669807{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0939979{col 71}{space 3} .5605542
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1218644{col 30}{space 2} .0874398{col 41}{space 1}    1.39{col 50}{space 3}0.163{col 58}{space 4}-.0495145{col 71}{space 3} .2932434
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2489504{col 30}{space 2} .0606888{col 41}{space 1}    4.10{col 50}{space 3}0.000{col 58}{space 4} .1300024{col 71}{space 3} .3678984
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1706053{col 30}{space 2} .0449678{col 41}{space 1}   -3.79{col 50}{space 3}0.000{col 58}{space 4}-.2587405{col 71}{space 3}-.0824701
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0801993{col 30}{space 2} .0340543{col 41}{space 1}    2.36{col 50}{space 3}0.019{col 58}{space 4} .0134541{col 71}{space 3} .1469445
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0918587{col 30}{space 2} .0622896{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4}-.0302267{col 71}{space 3} .2139442
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0794698{col 30}{space 2} .3183776{col 41}{space 1}    0.25{col 50}{space 3}0.803{col 58}{space 4}-.5445388{col 71}{space 3} .7034785
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6842878{col 30}{space 2}  .115112{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .4586725{col 71}{space 3} .9099032
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8771263{col 30}{space 2}  .211392{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .4628056{col 71}{space 3} 1.291447
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4021776{col 30}{space 2} .1290436{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .1492567{col 71}{space 3} .6550984
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3345044{col 30}{space 2} .1088994{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .1210655{col 71}{space 3} .5479432
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0121297{col 30}{space 2} .0728009{col 41}{space 1}   -0.17{col 50}{space 3}0.868{col 58}{space 4}-.1548168{col 71}{space 3} .1305574
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2396461{col 30}{space 2} .0607943{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .1204914{col 71}{space 3} .3588007
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1105184{col 30}{space 2} .0530274{col 41}{space 1}    2.08{col 50}{space 3}0.037{col 58}{space 4} .0065867{col 71}{space 3} .2144501
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.834968{col 30}{space 2} .4253146{col 41}{space 1}   13.72{col 50}{space 3}0.000{col 58}{space 4} 5.001367{col 71}{space 3} 6.668569
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72304178
         {txt}sigma_e {c |} {res} 1.2974831
             {txt}rho {c |} {res} .23695817{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0315                                         {txt}min = {res}         1
{txt}     between = {res}0.1773                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1288                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   830.43
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0252807{col 30}{space 2} .0496064{col 41}{space 1}   -0.51{col 50}{space 3}0.610{col 58}{space 4}-.1225076{col 71}{space 3} .0719461
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0000605{col 30}{space 2} .0003055{col 41}{space 1}    0.20{col 50}{space 3}0.843{col 58}{space 4}-.0005382{col 71}{space 3} .0006592
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0130421{col 30}{space 2} .0071537{col 41}{space 1}    1.82{col 50}{space 3}0.068{col 58}{space 4}-.0009789{col 71}{space 3} .0270631
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0821008{col 30}{space 2} .1159954{col 41}{space 1}   -0.71{col 50}{space 3}0.479{col 58}{space 4}-.3094477{col 71}{space 3} .1452461
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0033439{col 30}{space 2} .0015581{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0002901{col 71}{space 3} .0063976
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0455503{col 30}{space 2}  .068214{col 41}{space 1}    0.67{col 50}{space 3}0.504{col 58}{space 4}-.0881468{col 71}{space 3} .1792474
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .315282{col 30}{space 2} .0519468{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .2134681{col 71}{space 3} .4170958
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4481701{col 30}{space 2} .1457759{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .1624546{col 71}{space 3} .7338857
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0824413{col 30}{space 2} .0865824{col 41}{space 1}    0.95{col 50}{space 3}0.341{col 58}{space 4}-.0872571{col 71}{space 3} .2521398
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1549721{col 30}{space 2} .1822599{col 41}{space 1}    0.85{col 50}{space 3}0.395{col 58}{space 4}-.2022507{col 71}{space 3}  .512195
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2874518{col 30}{space 2} .1087852{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0742368{col 71}{space 3} .5006669
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1949707{col 30}{space 2} .0782784{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.3483935{col 71}{space 3}-.0415479
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1020553{col 30}{space 2} .0464901{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.1931742{col 71}{space 3}-.0109363
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0005306{col 30}{space 2} .0015296{col 41}{space 1}   -0.35{col 50}{space 3}0.729{col 58}{space 4}-.0035286{col 71}{space 3} .0024675
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .236351{col 30}{space 2} .2153353{col 41}{space 1}    1.10{col 50}{space 3}0.272{col 58}{space 4}-.1856984{col 71}{space 3} .6584004
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0723118{col 30}{space 2}  .173963{col 41}{space 1}   -0.42{col 50}{space 3}0.678{col 58}{space 4} -.413273{col 71}{space 3} .2686495
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2823598{col 30}{space 2} .1043214{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .0778936{col 71}{space 3} .4868261
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6609401{col 30}{space 2}   .19651{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4} .2757877{col 71}{space 3} 1.046093
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0043747{col 30}{space 2} .1347102{col 41}{space 1}   -0.03{col 50}{space 3}0.974{col 58}{space 4}-.2684018{col 71}{space 3} .2596523
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4496793{col 30}{space 2} .0955091{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .2624849{col 71}{space 3} .6368737
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1508684{col 30}{space 2} .0582972{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0366079{col 71}{space 3} .2651288
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2710259{col 30}{space 2} .0439441{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4}  .184897{col 71}{space 3} .3571548
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.667679{col 30}{space 2} .2038224{col 41}{space 1}   17.99{col 50}{space 3}0.000{col 58}{space 4} 3.268194{col 71}{space 3} 4.067163
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50174306
         {txt}sigma_e {c |} {res} 1.4322889
             {txt}rho {c |} {res} .10930287{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0388                                         {txt}min = {res}         1
{txt}     between = {res}0.3011                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2559                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3513.85
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0998057{col 30}{space 2} .0225095{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .0556878{col 71}{space 3} .1439236
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0034777{col 30}{space 2} .0003763{col 41}{space 1}   -9.24{col 50}{space 3}0.000{col 58}{space 4}-.0042152{col 71}{space 3}-.0027402
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  -.03033{col 30}{space 2} .0049409{col 41}{space 1}   -6.14{col 50}{space 3}0.000{col 58}{space 4} -.040014{col 71}{space 3}-.0206459
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1809637{col 30}{space 2} .0595338{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .0642796{col 71}{space 3} .2976478
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0060997{col 30}{space 2} .0010408{col 41}{space 1}    5.86{col 50}{space 3}0.000{col 58}{space 4} .0040598{col 71}{space 3} .0081396
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3252281{col 30}{space 2} .0433153{col 41}{space 1}    7.51{col 50}{space 3}0.000{col 58}{space 4} .2403317{col 71}{space 3} .4101245
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2142329{col 30}{space 2} .0299469{col 41}{space 1}    7.15{col 50}{space 3}0.000{col 58}{space 4} .1555381{col 71}{space 3} .2729277
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0213086{col 30}{space 2} .0457728{col 41}{space 1}   -0.47{col 50}{space 3}0.642{col 58}{space 4}-.1110216{col 71}{space 3} .0684045
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1473783{col 30}{space 2} .0439042{col 41}{space 1}    3.36{col 50}{space 3}0.001{col 58}{space 4} .0613277{col 71}{space 3} .2334289
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0743131{col 30}{space 2} .0563598{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-.0361501{col 71}{space 3} .1847763
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2316819{col 30}{space 2} .0675948{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .0991985{col 71}{space 3} .3641653
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3072345{col 30}{space 2} .0472086{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .2147074{col 71}{space 3} .3997616
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0497295{col 30}{space 2} .0481292{col 41}{space 1}    1.03{col 50}{space 3}0.301{col 58}{space 4} -.044602{col 71}{space 3} .1440609
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0058855{col 30}{space 2} .0061953{col 41}{space 1}   -0.95{col 50}{space 3}0.342{col 58}{space 4} -.018028{col 71}{space 3}  .006257
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2581702{col 30}{space 2} .0612332{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1381554{col 71}{space 3} .3781849
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1525605{col 30}{space 2}  .060396{col 41}{space 1}    2.53{col 50}{space 3}0.012{col 58}{space 4} .0341866{col 71}{space 3} .2709345
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7257961{col 30}{space 2} .0638595{col 41}{space 1}   11.37{col 50}{space 3}0.000{col 58}{space 4} .6006337{col 71}{space 3} .8509584
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8111047{col 30}{space 2} .0679414{col 41}{space 1}   11.94{col 50}{space 3}0.000{col 58}{space 4}  .677942{col 71}{space 3} .9442673
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1060974{col 30}{space 2} .0857345{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.0619391{col 71}{space 3} .2741339
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0677196{col 30}{space 2} .0594691{col 41}{space 1}   -1.14{col 50}{space 3}0.255{col 58}{space 4}-.1842769{col 71}{space 3} .0488377
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0766811{col 30}{space 2} .0305034{col 41}{space 1}   -2.51{col 50}{space 3}0.012{col 58}{space 4}-.1364666{col 71}{space 3}-.0168956
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.588825{col 30}{space 2} .0388031{col 41}{space 1}  -15.17{col 50}{space 3}0.000{col 58}{space 4}-.6648777{col 71}{space 3}-.5127724
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.557944{col 30}{space 2} .0399539{col 41}{space 1}  -13.96{col 50}{space 3}0.000{col 58}{space 4}-.6362523{col 71}{space 3}-.4796358
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4063698{col 30}{space 2} .0407884{col 41}{space 1}   -9.96{col 50}{space 3}0.000{col 58}{space 4}-.4863137{col 71}{space 3} -.326426
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  4.78674{col 30}{space 2} .1880999{col 41}{space 1}   25.45{col 50}{space 3}0.000{col 58}{space 4} 4.418071{col 71}{space 3}  5.15541
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84162972
         {txt}sigma_e {c |} {res} 1.2175835
             {txt}rho {c |} {res} .32331766{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0127                                         {txt}min = {res}         1
{txt}     between = {res}0.2164                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1610                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1532.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0178286{col 30}{space 2} .0284348{col 41}{space 1}   -0.63{col 50}{space 3}0.531{col 58}{space 4}-.0735598{col 71}{space 3} .0379025
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0002123{col 30}{space 2} .0011382{col 41}{space 1}    0.19{col 50}{space 3}0.852{col 58}{space 4}-.0020185{col 71}{space 3}  .002443
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0040293{col 30}{space 2} .0054548{col 41}{space 1}   -0.74{col 50}{space 3}0.460{col 58}{space 4}-.0147205{col 71}{space 3} .0066619
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0274855{col 30}{space 2} .0690853{col 41}{space 1}   -0.40{col 50}{space 3}0.691{col 58}{space 4}-.1628901{col 71}{space 3} .1079192
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0005767{col 30}{space 2} .0011102{col 41}{space 1}   -0.52{col 50}{space 3}0.603{col 58}{space 4}-.0027527{col 71}{space 3} .0015993
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0105355{col 30}{space 2} .0399456{col 41}{space 1}    0.26{col 50}{space 3}0.792{col 58}{space 4}-.0677564{col 71}{space 3} .0888274
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2642685{col 30}{space 2} .0364698{col 41}{space 1}    7.25{col 50}{space 3}0.000{col 58}{space 4} .1927891{col 71}{space 3}  .335748
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .215032{col 30}{space 2} .0915507{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4}  .035596{col 71}{space 3} .3944681
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2828451{col 30}{space 2} .0499665{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4} .1849125{col 71}{space 3} .3807778
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0328804{col 30}{space 2} .0590143{col 41}{space 1}    0.56{col 50}{space 3}0.577{col 58}{space 4}-.0827854{col 71}{space 3} .1485463
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1505772{col 30}{space 2} .0399424{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .0722914{col 71}{space 3} .2288629
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2213628{col 30}{space 2} .0421516{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .1387472{col 71}{space 3} .3039784
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1541257{col 30}{space 2} .0353829{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.2234748{col 71}{space 3}-.0847765
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0033629{col 30}{space 2} .0030436{col 41}{space 1}    1.10{col 50}{space 3}0.269{col 58}{space 4}-.0026025{col 71}{space 3} .0093283
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1309494{col 30}{space 2} .0327889{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .0666844{col 71}{space 3} .1952145
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3331123{col 30}{space 2} .1222542{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0934985{col 71}{space 3}  .572726
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4177738{col 30}{space 2} .0686097{col 41}{space 1}    6.09{col 50}{space 3}0.000{col 58}{space 4} .2833013{col 71}{space 3} .5522463
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4861937{col 30}{space 2} .0799406{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4}  .329513{col 71}{space 3} .6428744
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} -.054548{col 30}{space 2} .0581089{col 41}{space 1}   -0.94{col 50}{space 3}0.348{col 58}{space 4}-.1684394{col 71}{space 3} .0593434
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2770498{col 30}{space 2} .0602887{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .1588861{col 71}{space 3} .3952135
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0718039{col 30}{space 2} .0371914{col 41}{space 1}    1.93{col 50}{space 3}0.054{col 58}{space 4}-.0010899{col 71}{space 3} .1446978
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0243051{col 30}{space 2} .0390374{col 41}{space 1}    0.62{col 50}{space 3}0.534{col 58}{space 4}-.0522069{col 71}{space 3}  .100817
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  .026586{col 30}{space 2} .0350803{col 41}{space 1}    0.76{col 50}{space 3}0.449{col 58}{space 4}  -.04217{col 71}{space 3} .0953421
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0291299{col 30}{space 2} .0382838{col 41}{space 1}    0.76{col 50}{space 3}0.447{col 58}{space 4} -.045905{col 71}{space 3} .1041648
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.273906{col 30}{space 2}  .186824{col 41}{space 1}   22.88{col 50}{space 3}0.000{col 58}{space 4} 3.907737{col 71}{space 3} 4.640074
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75176372
         {txt}sigma_e {c |} {res} 1.2119831
             {txt}rho {c |} {res} .27784381{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0426                                         {txt}min = {res}         1
{txt}     between = {res}0.2855                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1846                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2126.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0194376{col 30}{space 2} .0176333{col 41}{space 1}    1.10{col 50}{space 3}0.270{col 58}{space 4} -.015123{col 71}{space 3} .0539982
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0002126{col 30}{space 2}   .00098{col 41}{space 1}   -0.22{col 50}{space 3}0.828{col 58}{space 4}-.0021333{col 71}{space 3} .0017082
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .022057{col 30}{space 2} .0056402{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0110024{col 71}{space 3} .0331116
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  -.02376{col 30}{space 2} .0622735{col 41}{space 1}   -0.38{col 50}{space 3}0.703{col 58}{space 4}-.1458139{col 71}{space 3} .0982938
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000077{col 30}{space 2} .0010643{col 41}{space 1}    0.07{col 50}{space 3}0.942{col 58}{space 4}-.0020089{col 71}{space 3} .0021629
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0271325{col 30}{space 2} .0354025{col 41}{space 1}    0.77{col 50}{space 3}0.443{col 58}{space 4}-.0422551{col 71}{space 3} .0965201
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .336528{col 30}{space 2} .0350657{col 41}{space 1}    9.60{col 50}{space 3}0.000{col 58}{space 4} .2678005{col 71}{space 3} .4052555
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2216222{col 30}{space 2} .0573777{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4}  .109164{col 71}{space 3} .3340803
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2386789{col 30}{space 2} .0383787{col 41}{space 1}    6.22{col 50}{space 3}0.000{col 58}{space 4}  .163458{col 71}{space 3} .3138998
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3605503{col 30}{space 2} .0387355{col 41}{space 1}    9.31{col 50}{space 3}0.000{col 58}{space 4} .2846301{col 71}{space 3} .4364704
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0351503{col 30}{space 2} .0312609{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}  -.02612{col 71}{space 3} .0964206
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1966327{col 30}{space 2} .0329732{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .1320064{col 71}{space 3} .2612589
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0248376{col 30}{space 2} .0254582{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0250596{col 71}{space 3} .0747347
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0026063{col 30}{space 2} .0018272{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.0009749{col 71}{space 3} .0061875
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0487087{col 30}{space 2} .0280982{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0063628{col 71}{space 3} .1037801
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .151705{col 30}{space 2} .0891174{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0229619{col 71}{space 3} .3263719
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .350128{col 30}{space 2} .0642895{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .2241229{col 71}{space 3} .4761331
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1908276{col 30}{space 2} .0723353{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0490529{col 71}{space 3} .3326022
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .083915{col 30}{space 2}  .057665{col 41}{space 1}    1.46{col 50}{space 3}0.146{col 58}{space 4}-.0291063{col 71}{space 3} .1969364
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2635816{col 30}{space 2}  .055637{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .1545351{col 71}{space 3} .3726282
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .2351062{col 30}{space 2} .0315548{col 41}{space 1}    7.45{col 50}{space 3}0.000{col 58}{space 4}   .17326{col 71}{space 3} .2969524
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1531695{col 30}{space 2} .0403944{col 41}{space 1}   -3.79{col 50}{space 3}0.000{col 58}{space 4}-.2323411{col 71}{space 3}-.0739979
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0731134{col 30}{space 2} .0359581{col 41}{space 1}   -2.03{col 50}{space 3}0.042{col 58}{space 4}  -.14359{col 71}{space 3}-.0026368
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3446112{col 30}{space 2} .0357832{col 41}{space 1}    9.63{col 50}{space 3}0.000{col 58}{space 4} .2744774{col 71}{space 3} .4147451
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0965332{col 30}{space 2}  .035775{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0264155{col 71}{space 3} .1666508
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2857364{col 30}{space 2} .0328583{col 41}{space 1}    8.70{col 50}{space 3}0.000{col 58}{space 4} .2213353{col 71}{space 3} .3501374
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.506101{col 30}{space 2} .1946998{col 41}{space 1}   12.87{col 50}{space 3}0.000{col 58}{space 4} 2.124497{col 71}{space 3} 2.887706
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7640364
         {txt}sigma_e {c |} {res} 1.2492224
             {txt}rho {c |} {res} .27223306{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S18_farmer.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist _cons)
{res}{txt}(note: file S18_farmer.rtf not found)
(output written to {browse  `"S18_farmer.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                Farmer sample with Heckman selection correction               *
. ********************************************************************************
. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. 
. 
. 
. egen mean_non_farmer=mean(non_farmer), by(country year)
{txt}
{com}. gen farmer_sample=non_farmer==0
{txt}
{com}. 
. 
. probit farmer_sample dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  mean_non_farmer i.country i.year

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-50558.795}  
Iteration 1:{space 3}log likelihood = {res: -37896.42}  
Iteration 2:{space 3}log likelihood = {res:-37553.297}  
Iteration 3:{space 3}log likelihood = {res: -37552.87}  
Iteration 4:{space 3}log likelihood = {res: -37552.87}  
{res}
{txt}Probit regression{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 49}LR chi2({res}26{txt}){col 67}= {res}  26011.85
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -37552.87{txt}{col 49}Pseudo R2{col 67}= {res}    0.2572

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  farmer_sample{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
dependent_share {c |}{col 17}{res}{space 2} .5616987{col 29}{space 2} .0213805{col 40}{space 1}   26.27{col 49}{space 3}0.000{col 57}{space 4} .5197936{col 70}{space 3} .6036038
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0114786{col 29}{space 2} .0003729{col 40}{space 1}   30.78{col 49}{space 3}0.000{col 57}{space 4} .0107477{col 70}{space 3} .0122095
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.4427193{col 29}{space 2} .0125819{col 40}{space 1}  -35.19{col 49}{space 3}0.000{col 57}{space 4}-.4673793{col 70}{space 3}-.4180592
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}-.2246008{col 29}{space 2} .0135783{col 40}{space 1}  -16.54{col 49}{space 3}0.000{col 57}{space 4}-.2512138{col 70}{space 3}-.1979878
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .4185873{col 29}{space 2}  .016238{col 40}{space 1}   25.78{col 49}{space 3}0.000{col 57}{space 4} .3867614{col 70}{space 3} .4504132
{txt}{space 10}phone {c |}{col 17}{res}{space 2}-.2442413{col 29}{space 2} .0137053{col 40}{space 1}  -17.82{col 49}{space 3}0.000{col 57}{space 4}-.2711031{col 70}{space 3}-.2173794
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.9918629{col 29}{space 2} .0122773{col 40}{space 1}  -80.79{col 49}{space 3}0.000{col 57}{space 4}-1.015926{col 70}{space 3}-.9677999
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.4293164{col 29}{space 2} .0116765{col 40}{space 1}  -36.77{col 49}{space 3}0.000{col 57}{space 4} -.452202{col 70}{space 3}-.4064308
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.2305025{col 29}{space 2} .0109481{col 40}{space 1}  -21.05{col 49}{space 3}0.000{col 57}{space 4}-.2519603{col 70}{space 3}-.2090446
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .7145495{col 29}{space 2} .0167792{col 40}{space 1}   42.59{col 49}{space 3}0.000{col 57}{space 4} .6816629{col 70}{space 3} .7474361
{txt}mean_non_farmer {c |}{col 17}{res}{space 2}-1.304516{col 29}{space 2}  .243744{col 40}{space 1}   -5.35{col 49}{space 3}0.000{col 57}{space 4}-1.782246{col 70}{space 3}-.8267869
{txt}{space 15} {c |}
{space 8}country {c |}
{space 7}Nigeria  {c |}{col 17}{res}{space 2}-.0221509{col 29}{space 2} .0355554{col 40}{space 1}   -0.62{col 49}{space 3}0.533{col 57}{space 4}-.0918381{col 70}{space 3} .0475363
{txt}{space 6}Ethiopia  {c |}{col 17}{res}{space 2} .1222104{col 29}{space 2} .0283253{col 40}{space 1}    4.31{col 49}{space 3}0.000{col 57}{space 4} .0666937{col 70}{space 3}  .177727
{txt}{space 8}Uganda  {c |}{col 17}{res}{space 2} .2309322{col 29}{space 2} .0305755{col 40}{space 1}    7.55{col 49}{space 3}0.000{col 57}{space 4} .1710054{col 70}{space 3}  .290859
{txt}{space 6}Tanzania  {c |}{col 17}{res}{space 2} .1554091{col 29}{space 2} .0301158{col 40}{space 1}    5.16{col 49}{space 3}0.000{col 57}{space 4} .0963832{col 70}{space 3} .2144351
{txt}{space 8}Malawi  {c |}{col 17}{res}{space 2}-.1456884{col 29}{space 2} .0354823{col 40}{space 1}   -4.11{col 49}{space 3}0.000{col 57}{space 4}-.2152323{col 70}{space 3}-.0761444
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.0693902{col 29}{space 2} .0469569{col 40}{space 1}   -1.48{col 49}{space 3}0.139{col 57}{space 4} -.161424{col 70}{space 3} .0226435
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .1090902{col 29}{space 2} .0329052{col 40}{space 1}    3.32{col 49}{space 3}0.001{col 57}{space 4} .0445973{col 70}{space 3} .1735832
{txt}{space 10}2011  {c |}{col 17}{res}{space 2}-.0745296{col 29}{space 2} .0367793{col 40}{space 1}   -2.03{col 49}{space 3}0.043{col 57}{space 4}-.1466157{col 70}{space 3}-.0024435
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1488564{col 29}{space 2} .0330255{col 40}{space 1}    4.51{col 49}{space 3}0.000{col 57}{space 4} .0841276{col 70}{space 3} .2135852
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .1894946{col 29}{space 2} .0398851{col 40}{space 1}    4.75{col 49}{space 3}0.000{col 57}{space 4} .1113212{col 70}{space 3} .2676681
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .0470369{col 29}{space 2} .0360904{col 40}{space 1}    1.30{col 49}{space 3}0.192{col 57}{space 4}-.0236989{col 70}{space 3} .1177728
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .2257556{col 29}{space 2} .0367046{col 40}{space 1}    6.15{col 49}{space 3}0.000{col 57}{space 4} .1538159{col 70}{space 3} .2976953
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .2151551{col 29}{space 2} .0509526{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .1152899{col 70}{space 3} .3150204
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .6061141{col 29}{space 2} .0410324{col 40}{space 1}   14.77{col 49}{space 3}0.000{col 57}{space 4} .5256922{col 70}{space 3}  .686536
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .5116036{col 29}{space 2} .0326827{col 40}{space 1}   15.65{col 49}{space 3}0.000{col 57}{space 4} .4475466{col 70}{space 3} .5756606
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .9538555{col 29}{space 2} .0682323{col 40}{space 1}   13.98{col 49}{space 3}0.000{col 57}{space 4} .8201227{col 70}{space 3} 1.087588
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. predict xb, xb
{txt}
{com}. gen double imr = normalden(xb)/normal(xb)
{txt}
{com}. drop if non_farmer==1
{txt}(22,521 observations deleted)

{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}      2,325        3.46        3.46
{txt}       2009 {c |}{res}      2,359        3.51        6.97
{txt}       2010 {c |}{res}      9,246       13.75       20.72
{txt}       2011 {c |}{res}      8,192       12.19       32.91
{txt}       2012 {c |}{res}      6,506        9.68       42.59
{txt}       2013 {c |}{res}      7,503       11.16       53.75
{txt}       2014 {c |}{res}      5,153        7.67       61.42
{txt}       2015 {c |}{res}      8,909       13.25       74.67
{txt}       2016 {c |}{res}      2,007        2.99       77.65
{txt}       2018 {c |}{res}      6,254        9.30       86.96
{txt}       2019 {c |}{res}      8,767       13.04      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     67,221      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  imr
{txt}
{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S11                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    67,221
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,842

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0301                                         {txt}min = {res}         1
{txt}     between = {res}0.3568                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2743                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 19989.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,842} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0493126{col 30}{space 2} .0031518{col 41}{space 1}   15.65{col 50}{space 3}0.000{col 58}{space 4} .0431352{col 71}{space 3} .0554899
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0113159{col 30}{space 2} .0024465{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4}-.0161109{col 71}{space 3}-.0065208
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0507543{col 30}{space 2} .0304588{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0089439{col 71}{space 3} .1104524
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0014329{col 30}{space 2} .0005052{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0004428{col 71}{space 3} .0024231
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0032776{col 30}{space 2} .0195842{col 41}{space 1}   -0.17{col 50}{space 3}0.867{col 58}{space 4}-.0416619{col 71}{space 3} .0351067
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2667382{col 30}{space 2} .0153689{col 41}{space 1}   17.36{col 50}{space 3}0.000{col 58}{space 4} .2366156{col 71}{space 3} .2968608
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .152947{col 30}{space 2} .0317532{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .0907118{col 71}{space 3} .2151821
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1688695{col 30}{space 2} .0193691{col 41}{space 1}    8.72{col 50}{space 3}0.000{col 58}{space 4} .1309068{col 71}{space 3} .2068323
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .081152{col 30}{space 2} .0343623{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0138032{col 71}{space 3} .1485008
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0940936{col 30}{space 2} .0216026{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0517532{col 71}{space 3} .1364339
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1874434{col 30}{space 2} .0181432{col 41}{space 1}   10.33{col 50}{space 3}0.000{col 58}{space 4} .1518833{col 71}{space 3} .2230035
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0124928{col 30}{space 2} .0187689{col 41}{space 1}   -0.67{col 50}{space 3}0.506{col 58}{space 4}-.0492792{col 71}{space 3} .0242937
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0010792{col 30}{space 2} .0009448{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0007725{col 71}{space 3}  .002931
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0481795{col 30}{space 2} .0159042{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0170079{col 71}{space 3}  .079351
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1203992{col 30}{space 2} .0401105{col 41}{space 1}    3.00{col 50}{space 3}0.003{col 58}{space 4} .0417841{col 71}{space 3} .1990144
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5297378{col 30}{space 2}  .027216{col 41}{space 1}   19.46{col 50}{space 3}0.000{col 58}{space 4} .4763954{col 71}{space 3} .5830802
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6026335{col 30}{space 2} .0311038{col 41}{space 1}   19.37{col 50}{space 3}0.000{col 58}{space 4} .5416712{col 71}{space 3} .6635958
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1726525{col 30}{space 2} .0287545{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .1162947{col 71}{space 3} .2290104
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1877996{col 30}{space 2} .0248856{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .1390247{col 71}{space 3} .2365744
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2884281{col 30}{space 2} .0667612{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .1575784{col 71}{space 3} .4192777
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0062154{col 30}{space 2} .0040395{col 41}{space 1}   -1.54{col 50}{space 3}0.124{col 58}{space 4}-.0141327{col 71}{space 3}  .001702
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.336351{col 30}{space 2} .0344728{col 41}{space 1}   -9.76{col 50}{space 3}0.000{col 58}{space 4}-.4039165{col 71}{space 3}-.2687856
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.413694{col 30}{space 2} .0337118{col 41}{space 1}  -41.93{col 50}{space 3}0.000{col 58}{space 4}-1.479768{col 71}{space 3} -1.34762
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3156399{col 30}{space 2} .0339664{col 41}{space 1}   -9.29{col 50}{space 3}0.000{col 58}{space 4}-.3822129{col 71}{space 3}-.2490669
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1506831{col 30}{space 2} .0324376{col 41}{space 1}   -4.65{col 50}{space 3}0.000{col 58}{space 4}-.2142596{col 71}{space 3}-.0871066
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6316101{col 30}{space 2} .0382714{col 41}{space 1}   16.50{col 50}{space 3}0.000{col 58}{space 4} .5565995{col 71}{space 3} .7066207
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2401456{col 30}{space 2} .0419798{col 41}{space 1}   -5.72{col 50}{space 3}0.000{col 58}{space 4}-.3224244{col 71}{space 3}-.1578668
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0148885{col 30}{space 2} .0310849{col 41}{space 1}   -0.48{col 50}{space 3}0.632{col 58}{space 4}-.0758137{col 71}{space 3} .0460368
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0534126{col 30}{space 2} .0358744{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0168998{col 71}{space 3} .1237251
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0193004{col 30}{space 2} .0316477{col 41}{space 1}    0.61{col 50}{space 3}0.542{col 58}{space 4}-.0427278{col 71}{space 3} .0813287
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1137733{col 30}{space 2} .0357201{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0437633{col 71}{space 3} .1837834
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0971862{col 30}{space 2} .0367592{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.1692329{col 71}{space 3}-.0251396
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1738341{col 30}{space 2} .0349714{col 41}{space 1}    4.97{col 50}{space 3}0.000{col 58}{space 4} .1052915{col 71}{space 3} .2423768
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1921565{col 30}{space 2} .0479058{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.2860502{col 71}{space 3}-.0982628
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5173363{col 30}{space 2} .0401613{col 41}{space 1}   12.88{col 50}{space 3}0.000{col 58}{space 4} .4386215{col 71}{space 3}  .596051
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0399915{col 30}{space 2} .0360206{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-.0306075{col 71}{space 3} .1105905
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.358377{col 30}{space 2} .0588455{col 41}{space 1}   74.06{col 50}{space 3}0.000{col 58}{space 4} 4.243042{col 71}{space 3} 4.473712
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78833537
         {txt}sigma_e {c |} {res} 1.2293182
             {txt}rho {c |} {res} .29140237{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,981
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,826

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0189                                         {txt}min = {res}         1
{txt}     between = {res}0.3014                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.1941                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1724.75
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,826} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0176846{col 30}{space 2} .0059247{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .0060724{col 71}{space 3} .0292968
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0359303{col 30}{space 2} .0076567{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0209234{col 71}{space 3} .0509372
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0405897{col 30}{space 2} .0676443{col 41}{space 1}    0.60{col 50}{space 3}0.548{col 58}{space 4}-.0919908{col 71}{space 3} .1731702
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022598{col 30}{space 2} .0011726{col 41}{space 1}   -1.93{col 50}{space 3}0.054{col 58}{space 4} -.004558{col 71}{space 3} .0000384
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0210673{col 30}{space 2} .0444387{col 41}{space 1}   -0.47{col 50}{space 3}0.635{col 58}{space 4}-.1081655{col 71}{space 3} .0660309
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .319158{col 30}{space 2} .0337851{col 41}{space 1}    9.45{col 50}{space 3}0.000{col 58}{space 4} .2529404{col 71}{space 3} .3853756
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1756942{col 30}{space 2} .1624121{col 41}{space 1}   -1.08{col 50}{space 3}0.279{col 58}{space 4}-.4940161{col 71}{space 3} .1426276
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1696264{col 30}{space 2} .0398051{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0916099{col 71}{space 3}  .247643
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1017186{col 30}{space 2} .0695666{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0346294{col 71}{space 3} .2380666
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .087175{col 30}{space 2} .0782686{col 41}{space 1}    1.11{col 50}{space 3}0.265{col 58}{space 4}-.0662287{col 71}{space 3} .2405788
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1916014{col 30}{space 2} .0535528{col 41}{space 1}    3.58{col 50}{space 3}0.000{col 58}{space 4} .0866398{col 71}{space 3} .2965629
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1255797{col 30}{space 2} .0423034{col 41}{space 1}   -2.97{col 50}{space 3}0.003{col 58}{space 4}-.2084927{col 71}{space 3}-.0426666
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0101946{col 30}{space 2} .0037642{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4}  .002817{col 71}{space 3} .0175722
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2326364{col 30}{space 2} .0335269{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4} .1669249{col 71}{space 3} .2983478
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9035758{col 30}{space 2} .2817333{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .3513886{col 71}{space 3} 1.455763
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .416516{col 30}{space 2} .0598763{col 41}{space 1}    6.96{col 50}{space 3}0.000{col 58}{space 4} .2991605{col 71}{space 3} .5338714
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3863801{col 30}{space 2} .0734838{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4} .2423545{col 71}{space 3} .5304057
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3495053{col 30}{space 2} .1149817{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .1241454{col 71}{space 3} .5748652
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1365183{col 30}{space 2} .0669943{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0052119{col 71}{space 3} .2678247
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .1643309{col 30}{space 2} .1608233{col 41}{space 1}    1.02{col 50}{space 3}0.307{col 58}{space 4}-.1508769{col 71}{space 3} .4795387
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0246457{col 30}{space 2} .0075304{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0098864{col 71}{space 3} .0394051
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1758554{col 30}{space 2} .0236874{col 41}{space 1}   -7.42{col 50}{space 3}0.000{col 58}{space 4}-.2222819{col 71}{space 3} -.129429
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.099629{col 30}{space 2} .0956399{col 41}{space 1}   32.41{col 50}{space 3}0.000{col 58}{space 4} 2.912178{col 71}{space 3} 3.287079
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7117056
         {txt}sigma_e {c |} {res} 1.0545808
             {txt}rho {c |} {res} .31292743{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,359
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0463                                         {txt}min = {res}         1
{txt}     between = {res}0.3466                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2626                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2229.87
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0935467{col 30}{space 2} .0109348{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .0721149{col 71}{space 3} .1149785
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0170301{col 30}{space 2} .0095615{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.0357702{col 71}{space 3}   .00171
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.372988{col 30}{space 2} .0893236{col 41}{space 1}   -4.18{col 50}{space 3}0.000{col 58}{space 4} -.548059{col 71}{space 3}-.1979171
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0050364{col 30}{space 2} .0014431{col 41}{space 1}   -3.49{col 50}{space 3}0.000{col 58}{space 4}-.0078649{col 71}{space 3} -.002208
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0153294{col 30}{space 2} .0532862{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.1197685{col 71}{space 3} .0891097
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3122737{col 30}{space 2} .0485863{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .2170462{col 71}{space 3} .4075012
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2649106{col 30}{space 2} .1607482{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0501502{col 71}{space 3} .5799713
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2676571{col 30}{space 2} .0592524{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .1515245{col 71}{space 3} .3837897
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6788486{col 30}{space 2} .1458043{col 41}{space 1}    4.66{col 50}{space 3}0.000{col 58}{space 4} .3930773{col 71}{space 3} .9646198
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .232853{col 30}{space 2} .0721912{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4}  .091361{col 71}{space 3} .3743451
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2991014{col 30}{space 2} .0487586{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .2035363{col 71}{space 3} .3946664
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.3111253{col 30}{space 2} .0520306{col 41}{space 1}   -5.98{col 50}{space 3}0.000{col 58}{space 4}-.4131034{col 71}{space 3}-.2091472
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0219108{col 30}{space 2} .0268859{col 41}{space 1}    0.81{col 50}{space 3}0.415{col 58}{space 4}-.0307847{col 71}{space 3} .0746063
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0725732{col 30}{space 2} .0485928{col 41}{space 1}   -1.49{col 50}{space 3}0.135{col 58}{space 4}-.1678134{col 71}{space 3}  .022667
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1132808{col 30}{space 2} .2275603{col 41}{space 1}    0.50{col 50}{space 3}0.619{col 58}{space 4}-.3327291{col 71}{space 3} .5592907
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .53001{col 30}{space 2} .0817213{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .3698392{col 71}{space 3} .6901808
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7993002{col 30}{space 2} .1448621{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .5153757{col 71}{space 3} 1.083225
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4296177{col 30}{space 2} .0918002{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4} .2496927{col 71}{space 3} .6095427
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3798456{col 30}{space 2} .0746737{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .2334878{col 71}{space 3} .5262034
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.5903767{col 30}{space 2} .2089754{col 41}{space 1}   -2.83{col 50}{space 3}0.005{col 58}{space 4} -.999961{col 71}{space 3}-.1807924
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0314161{col 30}{space 2}  .015952{col 41}{space 1}   -1.97{col 50}{space 3}0.049{col 58}{space 4}-.0626815{col 71}{space 3}-.0001507
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .215539{col 30}{space 2} .0508986{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .1157795{col 71}{space 3} .3152984
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1157502{col 30}{space 2} .0425022{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0324473{col 71}{space 3} .1990531
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.352471{col 30}{space 2} .1197503{col 41}{space 1}   44.70{col 50}{space 3}0.000{col 58}{space 4} 5.117764{col 71}{space 3} 5.587177
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69992936
         {txt}sigma_e {c |} {res} 1.3050849
             {txt}rho {c |} {res} .22337808{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,312
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,179

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0618                                         {txt}min = {res}         1
{txt}     between = {res}0.1770                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1379                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   893.51
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,179} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1563794{col 30}{space 2} .0189697{col 41}{space 1}    8.24{col 50}{space 3}0.000{col 58}{space 4} .1191995{col 71}{space 3} .1935592
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0096068{col 30}{space 2} .0073702{col 41}{space 1}    1.30{col 50}{space 3}0.192{col 58}{space 4}-.0048385{col 71}{space 3} .0240522
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0060129{col 30}{space 2} .1335716{col 41}{space 1}   -0.05{col 50}{space 3}0.964{col 58}{space 4}-.2678084{col 71}{space 3} .2557825
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0048423{col 30}{space 2} .0019286{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0010624{col 71}{space 3} .0086223
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0148175{col 30}{space 2} .0870294{col 41}{space 1}    0.17{col 50}{space 3}0.865{col 58}{space 4}-.1557569{col 71}{space 3}  .185392
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2511408{col 30}{space 2} .0579845{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1374932{col 71}{space 3} .3647883
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4585139{col 30}{space 2} .1508315{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .1628896{col 71}{space 3} .7541381
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0077925{col 30}{space 2} .0884833{col 41}{space 1}    0.09{col 50}{space 3}0.930{col 58}{space 4}-.1656316{col 71}{space 3} .1812167
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0112221{col 30}{space 2} .2364812{col 41}{space 1}   -0.05{col 50}{space 3}0.962{col 58}{space 4}-.4747168{col 71}{space 3} .4522727
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1737982{col 30}{space 2} .1194125{col 41}{space 1}    1.46{col 50}{space 3}0.146{col 58}{space 4}-.0602459{col 71}{space 3} .4078424
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2813764{col 30}{space 2} .0783787{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.4349958{col 71}{space 3} -.127757
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0461561{col 30}{space 2} .0773153{col 41}{space 1}   -0.60{col 50}{space 3}0.551{col 58}{space 4}-.1976913{col 71}{space 3} .1053791
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014702{col 30}{space 2} .0015784{col 41}{space 1}   -0.93{col 50}{space 3}0.352{col 58}{space 4}-.0045638{col 71}{space 3} .0016234
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1787293{col 30}{space 2} .2165634{col 41}{space 1}    0.83{col 50}{space 3}0.409{col 58}{space 4}-.2457271{col 71}{space 3} .6031857
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0229208{col 30}{space 2} .1704226{col 41}{space 1}    0.13{col 50}{space 3}0.893{col 58}{space 4}-.3111012{col 71}{space 3} .3569429
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .350856{col 30}{space 2} .1027657{col 41}{space 1}    3.41{col 50}{space 3}0.001{col 58}{space 4} .1494388{col 71}{space 3} .5522731
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6431547{col 30}{space 2} .1963901{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .2582372{col 71}{space 3} 1.028072
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0690256{col 30}{space 2} .1353752{col 41}{space 1}    0.51{col 50}{space 3}0.610{col 58}{space 4}-.1963049{col 71}{space 3} .3343561
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5397553{col 30}{space 2} .0931951{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .3570962{col 71}{space 3} .7224143
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4356463{col 30}{space 2} .3196765{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.1909082{col 71}{space 3} 1.062201
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.1351865{col 30}{space 2} .0222601{col 41}{space 1}   -6.07{col 50}{space 3}0.000{col 58}{space 4}-.1788156{col 71}{space 3}-.0915575
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2438884{col 30}{space 2} .0461677{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .1534013{col 71}{space 3} .3343755
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.247393{col 30}{space 2} .1790447{col 41}{space 1}   23.72{col 50}{space 3}0.000{col 58}{space 4} 3.896472{col 71}{space 3} 4.598314
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54676201
         {txt}sigma_e {c |} {res} 1.4176812
             {txt}rho {c |} {res} .12948404{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,882
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,309

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0380                                         {txt}min = {res}         1
{txt}     between = {res}0.2991                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2533                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3476.39
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,309} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0535286{col 30}{space 2}  .009687{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .0345425{col 71}{space 3} .0725148
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0303009{col 30}{space 2} .0049939{col 41}{space 1}   -6.07{col 50}{space 3}0.000{col 58}{space 4}-.0400887{col 71}{space 3} -.020513
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2792152{col 30}{space 2} .0695801{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .1428406{col 71}{space 3} .4155897
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0075957{col 30}{space 2} .0012244{col 41}{space 1}    6.20{col 50}{space 3}0.000{col 58}{space 4} .0051958{col 71}{space 3} .0099955
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2316198{col 30}{space 2} .0526962{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .1283372{col 71}{space 3} .3349025
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1749844{col 30}{space 2} .0327641{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4}  .110768{col 71}{space 3} .2392007
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0336362{col 30}{space 2} .0519166{col 41}{space 1}    0.65{col 50}{space 3}0.517{col 58}{space 4}-.0681185{col 71}{space 3} .1353908
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1068551{col 30}{space 2} .0457587{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0171698{col 71}{space 3} .1965404
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} -.091184{col 30}{space 2} .0910129{col 41}{space 1}   -1.00{col 50}{space 3}0.316{col 58}{space 4}-.2695659{col 71}{space 3}  .087198
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1618748{col 30}{space 2} .0740128{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0168123{col 71}{space 3} .3069372
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .275918{col 30}{space 2} .0492338{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .1794216{col 71}{space 3} .3724144
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1357712{col 30}{space 2} .0582035{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0216945{col 71}{space 3} .2498479
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0063925{col 30}{space 2} .0060207{col 41}{space 1}   -1.06{col 50}{space 3}0.288{col 58}{space 4}-.0181928{col 71}{space 3} .0054079
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3314914{col 30}{space 2} .0610269{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4}  .211881{col 71}{space 3} .4511018
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1608109{col 30}{space 2} .0601113{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0429949{col 71}{space 3} .2786269
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7502906{col 30}{space 2} .0636526{col 41}{space 1}   11.79{col 50}{space 3}0.000{col 58}{space 4} .6255338{col 71}{space 3} .8750474
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8111174{col 30}{space 2} .0682095{col 41}{space 1}   11.89{col 50}{space 3}0.000{col 58}{space 4} .6774292{col 71}{space 3} .9448056
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .093939{col 30}{space 2} .0842762{col 41}{space 1}    1.11{col 50}{space 3}0.265{col 58}{space 4}-.0712393{col 71}{space 3} .2591174
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0366636{col 30}{space 2} .0593737{col 41}{space 1}   -0.62{col 50}{space 3}0.537{col 58}{space 4}-.1530339{col 71}{space 3} .0797068
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3816313{col 30}{space 2} .1577561{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0724351{col 71}{space 3} .6908275
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} -.088315{col 30}{space 2} .0127585{col 41}{space 1}   -6.92{col 50}{space 3}0.000{col 58}{space 4}-.1133212{col 71}{space 3}-.0633088
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6394758{col 30}{space 2} .0537879{col 41}{space 1}  -11.89{col 50}{space 3}0.000{col 58}{space 4}-.7448981{col 71}{space 3}-.5340535
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.6130578{col 30}{space 2}  .052297{col 41}{space 1}  -11.72{col 50}{space 3}0.000{col 58}{space 4} -.715558{col 71}{space 3}-.5105575
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4297095{col 30}{space 2} .0485784{col 41}{space 1}   -8.85{col 50}{space 3}0.000{col 58}{space 4}-.5249215{col 71}{space 3}-.3344976
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.574994{col 30}{space 2} .0926676{col 41}{space 1}   49.37{col 50}{space 3}0.000{col 58}{space 4} 4.393369{col 71}{space 3} 4.756619
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84855245
         {txt}sigma_e {c |} {res} 1.2182207
             {txt}rho {c |} {res} .32668222{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,921
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,358

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0302                                         {txt}min = {res}         1
{txt}     between = {res}0.2411                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1927                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  2868.69
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,358} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0666303{col 30}{space 2}  .006046{col 41}{space 1}   11.02{col 50}{space 3}0.000{col 58}{space 4} .0547803{col 71}{space 3} .0784802
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0146487{col 30}{space 2} .0045622{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4}-.0235905{col 71}{space 3}-.0057068
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2228222{col 30}{space 2} .0643779{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .0966438{col 71}{space 3} .3490006
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0025459{col 30}{space 2} .0010322{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0005228{col 71}{space 3} .0045691
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1848445{col 30}{space 2} .0395521{col 41}{space 1}   -4.67{col 50}{space 3}0.000{col 58}{space 4}-.2623652{col 71}{space 3}-.1073237
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1653639{col 30}{space 2} .0325958{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4} .1014773{col 71}{space 3} .2292505
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4430547{col 30}{space 2} .0798613{col 41}{space 1}    5.55{col 50}{space 3}0.000{col 58}{space 4} .2865293{col 71}{space 3}   .59958
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1951594{col 30}{space 2} .0436217{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .1096624{col 71}{space 3} .2806563
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3602844{col 30}{space 2} .0684986{col 41}{space 1}   -5.26{col 50}{space 3}0.000{col 58}{space 4}-.4945392{col 71}{space 3}-.2260295
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0725357{col 30}{space 2} .0404294{col 41}{space 1}   -1.79{col 50}{space 3}0.073{col 58}{space 4}-.1517758{col 71}{space 3} .0067044
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1100049{col 30}{space 2} .0378954{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0357312{col 71}{space 3} .1842785
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1612547{col 30}{space 2} .0437139{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4}  .075577{col 71}{space 3} .2469324
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0028697{col 30}{space 2} .0019283{col 41}{space 1}    1.49{col 50}{space 3}0.137{col 58}{space 4}-.0009096{col 71}{space 3} .0066491
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0666585{col 30}{space 2} .0304773{col 41}{space 1}   -2.19{col 50}{space 3}0.029{col 58}{space 4}-.1263929{col 71}{space 3}-.0069241
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4070318{col 30}{space 2} .0962676{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .2183508{col 71}{space 3} .5957128
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4315741{col 30}{space 2} .0577211{col 41}{space 1}    7.48{col 50}{space 3}0.000{col 58}{space 4} .3184429{col 71}{space 3} .5447054
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4244133{col 30}{space 2} .0640217{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .2989332{col 71}{space 3} .5498935
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .042172{col 30}{space 2} .0479209{col 41}{space 1}    0.88{col 50}{space 3}0.379{col 58}{space 4}-.0517511{col 71}{space 3} .1360952
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2386046{col 30}{space 2}  .049803{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4} .1409925{col 71}{space 3} .3362167
{txt}{space 13}imr {c |}{col 18}{res}{space 2}  1.27984{col 30}{space 2} .1279321{col 41}{space 1}   10.00{col 50}{space 3}0.000{col 58}{space 4} 1.029098{col 71}{space 3} 1.530583
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0171775{col 30}{space 2} .0073167{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.0315178{col 71}{space 3}-.0028371
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0669324{col 30}{space 2} .0343301{col 41}{space 1}   -1.95{col 50}{space 3}0.051{col 58}{space 4}-.1342182{col 71}{space 3} .0003534
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0042701{col 30}{space 2} .0280096{col 41}{space 1}    0.15{col 50}{space 3}0.879{col 58}{space 4}-.0506277{col 71}{space 3} .0591679
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1541215{col 30}{space 2}  .037673{col 41}{space 1}   -4.09{col 50}{space 3}0.000{col 58}{space 4}-.2279593{col 71}{space 3}-.0802837
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.137604{col 30}{space 2} .0787585{col 41}{space 1}   52.54{col 50}{space 3}0.000{col 58}{space 4} 3.983241{col 71}{space 3} 4.291968
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75479914
         {txt}sigma_e {c |} {res} 1.2055002
             {txt}rho {c |} {res} .28162884{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,766
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0542                                         {txt}min = {res}         1
{txt}     between = {res}0.2898                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1850                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2567.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0556743{col 30}{space 2} .0061657{col 41}{space 1}    9.03{col 50}{space 3}0.000{col 58}{space 4} .0435898{col 71}{space 3} .0677589
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0035784{col 30}{space 2} .0054577{col 41}{space 1}    0.66{col 50}{space 3}0.512{col 58}{space 4}-.0071184{col 71}{space 3} .0142752
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0910252{col 30}{space 2}  .060842{col 41}{space 1}   -1.50{col 50}{space 3}0.135{col 58}{space 4}-.2102732{col 71}{space 3} .0282228
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028846{col 30}{space 2}  .001102{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4}-.0050444{col 71}{space 3}-.0007247
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1698946{col 30}{space 2} .0368535{col 41}{space 1}    4.61{col 50}{space 3}0.000{col 58}{space 4}  .097663{col 71}{space 3} .2421262
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3614774{col 30}{space 2} .0336244{col 41}{space 1}   10.75{col 50}{space 3}0.000{col 58}{space 4} .2955747{col 71}{space 3} .4273801
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0933207{col 30}{space 2} .0566932{col 41}{space 1}    1.65{col 50}{space 3}0.100{col 58}{space 4} -.017796{col 71}{space 3} .2044374
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2688604{col 30}{space 2} .0353564{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} .1995632{col 71}{space 3} .3381576
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5994729{col 30}{space 2} .0504223{col 41}{space 1}   11.89{col 50}{space 3}0.000{col 58}{space 4}  .500647{col 71}{space 3} .6982988
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1562603{col 30}{space 2} .0335571{col 41}{space 1}    4.66{col 50}{space 3}0.000{col 58}{space 4} .0904896{col 71}{space 3}  .222031
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2423582{col 30}{space 2}  .031312{col 41}{space 1}    7.74{col 50}{space 3}0.000{col 58}{space 4} .1809879{col 71}{space 3} .3037286
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1391687{col 30}{space 2} .0310879{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.2000999{col 71}{space 3}-.0782375
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0021363{col 30}{space 2} .0011618{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0001408{col 71}{space 3} .0044133
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0699292{col 30}{space 2} .0277618{col 41}{space 1}   -2.52{col 50}{space 3}0.012{col 58}{space 4}-.1243415{col 71}{space 3} -.015517
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1842006{col 30}{space 2} .0836511{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0202474{col 71}{space 3} .3481538
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3893843{col 30}{space 2}  .060758{col 41}{space 1}    6.41{col 50}{space 3}0.000{col 58}{space 4} .2703008{col 71}{space 3} .5084678
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .394969{col 30}{space 2} .0692597{col 41}{space 1}    5.70{col 50}{space 3}0.000{col 58}{space 4} .2592225{col 71}{space 3} .5307154
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1960549{col 30}{space 2}   .05578{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4}  .086728{col 71}{space 3} .3053817
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3085761{col 30}{space 2} .0535619{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .2035966{col 71}{space 3} .4135555
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.8183084{col 30}{space 2} .1260998{col 41}{space 1}   -6.49{col 50}{space 3}0.000{col 58}{space 4} -1.06546{col 71}{space 3}-.5711573
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0245457{col 30}{space 2} .0094894{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0059468{col 71}{space 3} .0431447
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1967223{col 30}{space 2} .0350867{col 41}{space 1}   -5.61{col 50}{space 3}0.000{col 58}{space 4}-.2654909{col 71}{space 3}-.1279537
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0146292{col 30}{space 2} .0349175{col 41}{space 1}   -0.42{col 50}{space 3}0.675{col 58}{space 4}-.0830662{col 71}{space 3} .0538077
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3931008{col 30}{space 2} .0326775{col 41}{space 1}   12.03{col 50}{space 3}0.000{col 58}{space 4}  .329054{col 71}{space 3} .4571476
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1336718{col 30}{space 2} .0330103{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4} .0689727{col 71}{space 3} .1983709
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2668202{col 30}{space 2} .0323592{col 41}{space 1}    8.25{col 50}{space 3}0.000{col 58}{space 4} .2033974{col 71}{space 3}  .330243
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.094183{col 30}{space 2} .0908993{col 41}{space 1}   45.04{col 50}{space 3}0.000{col 58}{space 4} 3.916024{col 71}{space 3} 4.272343
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .77456014
         {txt}sigma_e {c |} {res} 1.2440232
             {txt}rho {c |} {res} .27936348{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S11_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean _cons)
{res}{txt}(note: file S11_farmer_imr.rtf not found)
(output written to {browse  `"S11_farmer_imr.rtf"'})

{com}. 
. 
. 
. 
. ********************************************************************************
. *                                   S12                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    67,221
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,842

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0333                                         {txt}min = {res}         1
{txt}     between = {res}0.3617                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2800                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20929.07
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,842} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1196476{col 30}{space 2} .0060455{col 41}{space 1}   19.79{col 50}{space 3}0.000{col 58}{space 4} .1077986{col 71}{space 3} .1314966
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0130214{col 30}{space 2}  .002425{col 41}{space 1}   -5.37{col 50}{space 3}0.000{col 58}{space 4}-.0177743{col 71}{space 3}-.0082686
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0532018{col 30}{space 2} .0303331{col 41}{space 1}    1.75{col 50}{space 3}0.079{col 58}{space 4}  -.00625{col 71}{space 3} .1126535
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0014746{col 30}{space 2} .0005012{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .0004923{col 71}{space 3}  .002457
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0088862{col 30}{space 2} .0194579{col 41}{space 1}   -0.46{col 50}{space 3}0.648{col 58}{space 4}-.0470229{col 71}{space 3} .0292506
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2592719{col 30}{space 2} .0152906{col 41}{space 1}   16.96{col 50}{space 3}0.000{col 58}{space 4} .2293029{col 71}{space 3}  .289241
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1605207{col 30}{space 2} .0317039{col 41}{space 1}    5.06{col 50}{space 3}0.000{col 58}{space 4} .0983821{col 71}{space 3} .2226592
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1637897{col 30}{space 2} .0193519{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .1258607{col 71}{space 3} .2017186
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0576428{col 30}{space 2} .0343032{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0095902{col 71}{space 3} .1248757
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0875946{col 30}{space 2} .0215653{col 41}{space 1}    4.06{col 50}{space 3}0.000{col 58}{space 4} .0453274{col 71}{space 3} .1298619
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1844375{col 30}{space 2} .0181105{col 41}{space 1}   10.18{col 50}{space 3}0.000{col 58}{space 4} .1489417{col 71}{space 3} .2199334
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0062125{col 30}{space 2} .0187082{col 41}{space 1}   -0.33{col 50}{space 3}0.740{col 58}{space 4}  -.04288{col 71}{space 3}  .030455
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0007431{col 30}{space 2} .0009489{col 41}{space 1}    0.78{col 50}{space 3}0.434{col 58}{space 4}-.0011167{col 71}{space 3} .0026029
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0884946{col 30}{space 2} .0149201{col 41}{space 1}    5.93{col 50}{space 3}0.000{col 58}{space 4} .0592517{col 71}{space 3} .1177376
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1146644{col 30}{space 2} .0400614{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0361454{col 71}{space 3} .1931833
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .524396{col 30}{space 2} .0271308{col 41}{space 1}   19.33{col 50}{space 3}0.000{col 58}{space 4} .4712206{col 71}{space 3} .5775714
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6223803{col 30}{space 2} .0309919{col 41}{space 1}   20.08{col 50}{space 3}0.000{col 58}{space 4} .5616373{col 71}{space 3} .6831233
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1818799{col 30}{space 2} .0286729{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4}  .125682{col 71}{space 3} .2380778
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .192652{col 30}{space 2} .0247903{col 41}{space 1}    7.77{col 50}{space 3}0.000{col 58}{space 4} .1440639{col 71}{space 3} .2412402
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3310648{col 30}{space 2} .0666583{col 41}{space 1}    4.97{col 50}{space 3}0.000{col 58}{space 4}  .200417{col 71}{space 3} .4617127
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0102968{col 30}{space 2} .0084512{col 41}{space 1}    1.22{col 50}{space 3}0.223{col 58}{space 4}-.0062672{col 71}{space 3} .0268607
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.368476{col 30}{space 2} .0343927{col 41}{space 1}  -10.71{col 50}{space 3}0.000{col 58}{space 4}-.4358845{col 71}{space 3}-.3010675
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.486733{col 30}{space 2} .0336174{col 41}{space 1}  -44.23{col 50}{space 3}0.000{col 58}{space 4}-1.552622{col 71}{space 3}-1.420844
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4119973{col 30}{space 2} .0342548{col 41}{space 1}  -12.03{col 50}{space 3}0.000{col 58}{space 4}-.4791355{col 71}{space 3}-.3448591
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2438113{col 30}{space 2}  .032854{col 41}{space 1}   -7.42{col 50}{space 3}0.000{col 58}{space 4} -.308204{col 71}{space 3}-.1794186
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .515874{col 30}{space 2} .0385088{col 41}{space 1}   13.40{col 50}{space 3}0.000{col 58}{space 4} .4403981{col 71}{space 3} .5913498
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1797513{col 30}{space 2} .0419633{col 41}{space 1}   -4.28{col 50}{space 3}0.000{col 58}{space 4}-.2619979{col 71}{space 3}-.0975046
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0226295{col 30}{space 2} .0310502{col 41}{space 1}    0.73{col 50}{space 3}0.466{col 58}{space 4}-.0382277{col 71}{space 3} .0834867
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0763676{col 30}{space 2} .0358191{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0061635{col 71}{space 3} .1465718
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0496006{col 30}{space 2} .0316462{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0124248{col 71}{space 3}  .111626
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1386874{col 30}{space 2} .0356136{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4}  .068886{col 71}{space 3} .2084887
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0818338{col 30}{space 2} .0366535{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}-.1536734{col 71}{space 3}-.0099942
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1975562{col 30}{space 2} .0349238{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4} .1291069{col 71}{space 3} .2660056
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1472928{col 30}{space 2} .0480321{col 41}{space 1}   -3.07{col 50}{space 3}0.002{col 58}{space 4} -.241434{col 71}{space 3}-.0531515
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5452505{col 30}{space 2}  .040101{col 41}{space 1}   13.60{col 50}{space 3}0.000{col 58}{space 4}  .466654{col 71}{space 3} .6238469
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0706049{col 30}{space 2} .0359666{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0001117{col 71}{space 3} .1410982
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  4.21086{col 30}{space 2} .0594085{col 41}{space 1}   70.88{col 50}{space 3}0.000{col 58}{space 4} 4.094421{col 71}{space 3} 4.327298
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78314614
         {txt}sigma_e {c |} {res} 1.2274512
             {txt}rho {c |} {res} .28930714{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,981
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,826

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0216                                         {txt}min = {res}         1
{txt}     between = {res}0.3135                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2069                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1907.92
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,826} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0611269{col 30}{space 2} .0116242{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4}  .038344{col 71}{space 3} .0839098
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0301435{col 30}{space 2} .0075765{col 41}{space 1}    3.98{col 50}{space 3}0.000{col 58}{space 4} .0152938{col 71}{space 3} .0449931
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0503796{col 30}{space 2} .0670446{col 41}{space 1}    0.75{col 50}{space 3}0.452{col 58}{space 4}-.0810254{col 71}{space 3} .1817846
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0016277{col 30}{space 2} .0011576{col 41}{space 1}   -1.41{col 50}{space 3}0.160{col 58}{space 4}-.0038965{col 71}{space 3} .0006411
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0301043{col 30}{space 2} .0438991{col 41}{space 1}   -0.69{col 50}{space 3}0.493{col 58}{space 4}-.1161451{col 71}{space 3} .0559364
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .301523{col 30}{space 2} .0334766{col 41}{space 1}    9.01{col 50}{space 3}0.000{col 58}{space 4} .2359101{col 71}{space 3} .3671359
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1811638{col 30}{space 2} .1629376{col 41}{space 1}   -1.11{col 50}{space 3}0.266{col 58}{space 4}-.5005156{col 71}{space 3}  .138188
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1599371{col 30}{space 2} .0396936{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4}  .082139{col 71}{space 3} .2377351
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0585062{col 30}{space 2} .0695772{col 41}{space 1}    0.84{col 50}{space 3}0.400{col 58}{space 4}-.0778627{col 71}{space 3} .1948751
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0696796{col 30}{space 2} .0781923{col 41}{space 1}    0.89{col 50}{space 3}0.373{col 58}{space 4}-.0835745{col 71}{space 3} .2229337
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1883278{col 30}{space 2} .0534677{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4}  .083533{col 71}{space 3} .2931225
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0971908{col 30}{space 2} .0422097{col 41}{space 1}   -2.30{col 50}{space 3}0.021{col 58}{space 4}-.1799203{col 71}{space 3}-.0144613
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0083387{col 30}{space 2} .0037103{col 41}{space 1}    2.25{col 50}{space 3}0.025{col 58}{space 4} .0010667{col 71}{space 3} .0156107
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2133375{col 30}{space 2} .0312317{col 41}{space 1}    6.83{col 50}{space 3}0.000{col 58}{space 4} .1521245{col 71}{space 3} .2745504
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9310675{col 30}{space 2}  .287078{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4}  .368405{col 71}{space 3}  1.49373
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4215176{col 30}{space 2} .0593942{col 41}{space 1}    7.10{col 50}{space 3}0.000{col 58}{space 4} .3051072{col 71}{space 3}  .537928
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4288192{col 30}{space 2} .0730373{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .2856687{col 71}{space 3} .5719697
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3953044{col 30}{space 2} .1149386{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} .1700289{col 71}{space 3} .6205798
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1282349{col 30}{space 2} .0668265{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0027426{col 71}{space 3} .2592124
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2662471{col 30}{space 2} .1606029{col 41}{space 1}    1.66{col 50}{space 3}0.097{col 58}{space 4}-.0485288{col 71}{space 3}  .581023
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0895626{col 30}{space 2} .0163017{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .0576119{col 71}{space 3} .1215133
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} -.173994{col 30}{space 2} .0230154{col 41}{space 1}   -7.56{col 50}{space 3}0.000{col 58}{space 4}-.2191034{col 71}{space 3}-.1288847
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.819733{col 30}{space 2}  .098245{col 41}{space 1}   28.70{col 50}{space 3}0.000{col 58}{space 4} 2.627176{col 71}{space 3}  3.01229
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70099694
         {txt}sigma_e {c |} {res} 1.0536527
             {txt}rho {c |} {res} .30681981{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,359
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0440                                         {txt}min = {res}         1
{txt}     between = {res}0.3468                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2620                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2208.00
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1247659{col 30}{space 2}   .01653{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .0923677{col 71}{space 3} .1571641
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0177085{col 30}{space 2} .0095471{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-.0364204{col 71}{space 3} .0010034
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3746367{col 30}{space 2} .0895021{col 41}{space 1}   -4.19{col 50}{space 3}0.000{col 58}{space 4}-.5500575{col 71}{space 3}-.1992158
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0049137{col 30}{space 2} .0014378{col 41}{space 1}   -3.42{col 50}{space 3}0.001{col 58}{space 4}-.0077318{col 71}{space 3}-.0020956
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0210473{col 30}{space 2} .0534078{col 41}{space 1}   -0.39{col 50}{space 3}0.694{col 58}{space 4}-.1257248{col 71}{space 3} .0836301
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3037899{col 30}{space 2} .0485718{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .2085909{col 71}{space 3} .3989889
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2897668{col 30}{space 2} .1608695{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0255317{col 71}{space 3} .6050653
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2673369{col 30}{space 2} .0595186{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1506826{col 71}{space 3} .3839912
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6660438{col 30}{space 2} .1460018{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .3798854{col 71}{space 3} .9522021
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2195772{col 30}{space 2} .0723516{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0777707{col 71}{space 3} .3613837
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .296535{col 30}{space 2} .0488004{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4}  .200888{col 71}{space 3} .3921819
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.3051012{col 30}{space 2} .0521799{col 41}{space 1}   -5.85{col 50}{space 3}0.000{col 58}{space 4}-.4073719{col 71}{space 3}-.2028305
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0312165{col 30}{space 2} .0267977{col 41}{space 1}    1.16{col 50}{space 3}0.244{col 58}{space 4}-.0213061{col 71}{space 3} .0837391
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0233877{col 30}{space 2}  .047416{col 41}{space 1}    0.49{col 50}{space 3}0.622{col 58}{space 4}-.0695459{col 71}{space 3} .1163214
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1060589{col 30}{space 2} .2275952{col 41}{space 1}    0.47{col 50}{space 3}0.641{col 58}{space 4}-.3400195{col 71}{space 3} .5521373
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5149151{col 30}{space 2} .0821025{col 41}{space 1}    6.27{col 50}{space 3}0.000{col 58}{space 4} .3539971{col 71}{space 3}  .675833
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8204746{col 30}{space 2} .1452973{col 41}{space 1}    5.65{col 50}{space 3}0.000{col 58}{space 4} .5356971{col 71}{space 3} 1.105252
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4328478{col 30}{space 2} .0916671{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .2531836{col 71}{space 3} .6125119
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3808113{col 30}{space 2} .0746005{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4}  .234597{col 71}{space 3} .5270257
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.5513205{col 30}{space 2} .2098004{col 41}{space 1}   -2.63{col 50}{space 3}0.009{col 58}{space 4}-.9625217{col 71}{space 3}-.1401193
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0199973{col 30}{space 2} .0263006{col 41}{space 1}   -0.76{col 50}{space 3}0.447{col 58}{space 4}-.0715455{col 71}{space 3} .0315509
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2089999{col 30}{space 2} .0507807{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .1094717{col 71}{space 3} .3085282
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1333346{col 30}{space 2} .0423805{col 41}{space 1}    3.15{col 50}{space 3}0.002{col 58}{space 4} .0502703{col 71}{space 3}  .216399
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.256373{col 30}{space 2} .1252991{col 41}{space 1}   41.95{col 50}{space 3}0.000{col 58}{space 4} 5.010792{col 71}{space 3} 5.501955
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69792495
         {txt}sigma_e {c |} {res}  1.306342
             {txt}rho {c |} {res} .22205182{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,312
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,179

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0547                                         {txt}min = {res}         1
{txt}     between = {res}0.1775                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1370                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   890.89
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,179} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2859718{col 30}{space 2} .0396235{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .2083112{col 71}{space 3} .3636324
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0092246{col 30}{space 2} .0072947{col 41}{space 1}    1.26{col 50}{space 3}0.206{col 58}{space 4}-.0050728{col 71}{space 3}  .023522
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0014573{col 30}{space 2} .1335687{col 41}{space 1}   -0.01{col 50}{space 3}0.991{col 58}{space 4}-.2632472{col 71}{space 3} .2603326
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0050033{col 30}{space 2}  .001927{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0012264{col 71}{space 3} .0087802
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0256536{col 30}{space 2} .0864635{col 41}{space 1}    0.30{col 50}{space 3}0.767{col 58}{space 4}-.1438117{col 71}{space 3} .1951188
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2582403{col 30}{space 2}  .057874{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .1448093{col 71}{space 3} .3716712
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4431761{col 30}{space 2} .1502483{col 41}{space 1}    2.95{col 50}{space 3}0.003{col 58}{space 4} .1486949{col 71}{space 3} .7376573
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0165631{col 30}{space 2}  .088959{col 41}{space 1}    0.19{col 50}{space 3}0.852{col 58}{space 4}-.1577933{col 71}{space 3} .1909194
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0069695{col 30}{space 2} .2333747{col 41}{space 1}    0.03{col 50}{space 3}0.976{col 58}{space 4}-.4504366{col 71}{space 3} .4643755
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1973712{col 30}{space 2} .1178532{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0336168{col 71}{space 3} .4283592
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2554318{col 30}{space 2} .0784266{col 41}{space 1}   -3.26{col 50}{space 3}0.001{col 58}{space 4}-.4091452{col 71}{space 3}-.1017185
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0482027{col 30}{space 2} .0770889{col 41}{space 1}   -0.63{col 50}{space 3}0.532{col 58}{space 4}-.1992942{col 71}{space 3} .1028887
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0015302{col 30}{space 2}  .001568{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-.0046033{col 71}{space 3}  .001543
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2619181{col 30}{space 2} .2137081{col 41}{space 1}    1.23{col 50}{space 3}0.220{col 58}{space 4}-.1569422{col 71}{space 3} .6807783
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0418498{col 30}{space 2} .1700942{col 41}{space 1}    0.25{col 50}{space 3}0.806{col 58}{space 4}-.2915286{col 71}{space 3} .3752283
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3371375{col 30}{space 2} .1032782{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .1347159{col 71}{space 3}  .539559
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6514314{col 30}{space 2} .1927477{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .2736528{col 71}{space 3}  1.02921
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0475659{col 30}{space 2} .1338186{col 41}{space 1}    0.36{col 50}{space 3}0.722{col 58}{space 4}-.2147137{col 71}{space 3} .3098456
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4994876{col 30}{space 2} .0931902{col 41}{space 1}    5.36{col 50}{space 3}0.000{col 58}{space 4} .3168381{col 71}{space 3} .6821371
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4409969{col 30}{space 2} .3193627{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.1849424{col 71}{space 3} 1.066936
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2049222{col 30}{space 2} .0472294{col 41}{space 1}   -4.34{col 50}{space 3}0.000{col 58}{space 4}-.2974902{col 71}{space 3}-.1123542
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .268785{col 30}{space 2}  .046294{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .1780504{col 71}{space 3} .3595197
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.121898{col 30}{space 2} .1854166{col 41}{space 1}   22.23{col 50}{space 3}0.000{col 58}{space 4} 3.758488{col 71}{space 3} 4.485308
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .53640843
         {txt}sigma_e {c |} {res} 1.4224985
             {txt}rho {c |} {res} .12449357{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,882
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,309

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0392                                         {txt}min = {res}         1
{txt}     between = {res}0.2986                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2542                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3502.35
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,309} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1205186{col 30}{space 2} .0177789{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4} .0856726{col 71}{space 3} .1553646
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0357963{col 30}{space 2}   .00493{col 41}{space 1}   -7.26{col 50}{space 3}0.000{col 58}{space 4}-.0454589{col 71}{space 3}-.0261337
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2764373{col 30}{space 2} .0695559{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .1401103{col 71}{space 3} .4127644
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0071604{col 30}{space 2} .0012234{col 41}{space 1}    5.85{col 50}{space 3}0.000{col 58}{space 4} .0047625{col 71}{space 3} .0095583
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2405313{col 30}{space 2} .0524999{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .1376333{col 71}{space 3} .3434292
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1683612{col 30}{space 2} .0327994{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .1040756{col 71}{space 3} .2326468
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0416718{col 30}{space 2} .0518639{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.0599796{col 71}{space 3} .1433233
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1076849{col 30}{space 2} .0457852{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0179476{col 71}{space 3} .1974222
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0928726{col 30}{space 2} .0910119{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.2712527{col 71}{space 3} .0855075
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1670172{col 30}{space 2} .0739538{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0220704{col 71}{space 3}  .311964
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2780506{col 30}{space 2} .0489506{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4} .1821092{col 71}{space 3}  .373992
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1291449{col 30}{space 2} .0580961{col 41}{space 1}    2.22{col 50}{space 3}0.026{col 58}{space 4} .0152787{col 71}{space 3} .2430112
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0085982{col 30}{space 2} .0068409{col 41}{space 1}   -1.26{col 50}{space 3}0.209{col 58}{space 4}-.0220061{col 71}{space 3} .0048097
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3343154{col 30}{space 2} .0607832{col 41}{space 1}    5.50{col 50}{space 3}0.000{col 58}{space 4} .2151825{col 71}{space 3} .4534483
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .123456{col 30}{space 2} .0601227{col 41}{space 1}    2.05{col 50}{space 3}0.040{col 58}{space 4} .0056177{col 71}{space 3} .2412942
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7714579{col 30}{space 2} .0634983{col 41}{space 1}   12.15{col 50}{space 3}0.000{col 58}{space 4} .6470036{col 71}{space 3} .8959123
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8578034{col 30}{space 2} .0680656{col 41}{space 1}   12.60{col 50}{space 3}0.000{col 58}{space 4} .7243974{col 71}{space 3} .9912095
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1205609{col 30}{space 2} .0841082{col 41}{space 1}    1.43{col 50}{space 3}0.152{col 58}{space 4}-.0442881{col 71}{space 3} .2854099
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0470744{col 30}{space 2} .0590668{col 41}{space 1}   -0.80{col 50}{space 3}0.425{col 58}{space 4}-.1628432{col 71}{space 3} .0686944
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3790184{col 30}{space 2} .1575952{col 41}{space 1}    2.41{col 50}{space 3}0.016{col 58}{space 4} .0701374{col 71}{space 3} .6878994
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0633879{col 30}{space 2} .0242331{col 41}{space 1}   -2.62{col 50}{space 3}0.009{col 58}{space 4}-.1108839{col 71}{space 3}-.0158919
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6538218{col 30}{space 2} .0536674{col 41}{space 1}  -12.18{col 50}{space 3}0.000{col 58}{space 4} -.759008{col 71}{space 3}-.5486355
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.6241762{col 30}{space 2} .0521675{col 41}{space 1}  -11.96{col 50}{space 3}0.000{col 58}{space 4}-.7264227{col 71}{space 3}-.5219297
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4418918{col 30}{space 2}  .048562{col 41}{space 1}   -9.10{col 50}{space 3}0.000{col 58}{space 4}-.5370717{col 71}{space 3} -.346712
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.332882{col 30}{space 2} .0949566{col 41}{space 1}   45.63{col 50}{space 3}0.000{col 58}{space 4} 4.146771{col 71}{space 3} 4.518993
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84993587
         {txt}sigma_e {c |} {res} 1.2172896
             {txt}rho {c |} {res} .32773611{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,921
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,358

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0416                                         {txt}min = {res}         1
{txt}     between = {res}0.2449                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1984                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  2987.47
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,358} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1833199{col 30}{space 2}  .012548{col 41}{space 1}   14.61{col 50}{space 3}0.000{col 58}{space 4} .1587263{col 71}{space 3} .2079134
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0160566{col 30}{space 2} .0045775{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.0250283{col 71}{space 3}-.0070849
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2124895{col 30}{space 2}  .064369{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4} .0863287{col 71}{space 3} .3386503
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029489{col 30}{space 2} .0010224{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4}  .000945{col 71}{space 3} .0049527
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1814688{col 30}{space 2} .0393086{col 41}{space 1}   -4.62{col 50}{space 3}0.000{col 58}{space 4}-.2585122{col 71}{space 3}-.1044253
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1757563{col 30}{space 2} .0324823{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .1120922{col 71}{space 3} .2394203
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4248466{col 30}{space 2} .0790206{col 41}{space 1}    5.38{col 50}{space 3}0.000{col 58}{space 4}  .269969{col 71}{space 3} .5797242
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1843936{col 30}{space 2}  .043429{col 41}{space 1}    4.25{col 50}{space 3}0.000{col 58}{space 4} .0992744{col 71}{space 3} .2695128
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3668414{col 30}{space 2} .0679781{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4} -.500076{col 71}{space 3}-.2336068
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.077413{col 30}{space 2} .0402273{col 41}{space 1}   -1.92{col 50}{space 3}0.054{col 58}{space 4} -.156257{col 71}{space 3} .0014311
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1058333{col 30}{space 2} .0376857{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0319708{col 71}{space 3} .1796959
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1564934{col 30}{space 2} .0433698{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .0714901{col 71}{space 3} .2414966
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0024251{col 30}{space 2}  .001942{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0013812{col 71}{space 3} .0062314
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0198209{col 30}{space 2} .0279769{col 41}{space 1}    0.71{col 50}{space 3}0.479{col 58}{space 4}-.0350129{col 71}{space 3} .0746547
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4270429{col 30}{space 2} .0957647{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .2393475{col 71}{space 3} .6147384
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4415541{col 30}{space 2}  .057583{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .3286935{col 71}{space 3} .5544147
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4450868{col 30}{space 2}  .063932{col 41}{space 1}    6.96{col 50}{space 3}0.000{col 58}{space 4} .3197824{col 71}{space 3} .5703912
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0504695{col 30}{space 2} .0477403{col 41}{space 1}    1.06{col 50}{space 3}0.290{col 58}{space 4}-.0430997{col 71}{space 3} .1440386
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2424255{col 30}{space 2} .0496674{col 41}{space 1}    4.88{col 50}{space 3}0.000{col 58}{space 4} .1450791{col 71}{space 3} .3397719
{txt}{space 13}imr {c |}{col 18}{res}{space 2}  1.27043{col 30}{space 2} .1268406{col 41}{space 1}   10.02{col 50}{space 3}0.000{col 58}{space 4} 1.021827{col 71}{space 3} 1.519033
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0689505{col 30}{space 2} .0160454{col 41}{space 1}   -4.30{col 50}{space 3}0.000{col 58}{space 4}-.1003989{col 71}{space 3}-.0375022
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.1046284{col 30}{space 2} .0344444{col 41}{space 1}   -3.04{col 50}{space 3}0.002{col 58}{space 4}-.1721382{col 71}{space 3}-.0371186
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0038241{col 30}{space 2} .0279407{col 41}{space 1}    0.14{col 50}{space 3}0.891{col 58}{space 4}-.0509388{col 71}{space 3} .0585869
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1680191{col 30}{space 2}  .037407{col 41}{space 1}   -4.49{col 50}{space 3}0.000{col 58}{space 4}-.2413355{col 71}{space 3}-.0947027
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.989839{col 30}{space 2} .0819872{col 41}{space 1}   48.66{col 50}{space 3}0.000{col 58}{space 4} 3.829147{col 71}{space 3} 4.150531
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75738516
         {txt}sigma_e {c |} {res} 1.1983333
             {txt}rho {c |} {res} .28544104{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,766
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0555                                         {txt}min = {res}         1
{txt}     between = {res}0.2980                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1917                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2677.13
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1145762{col 30}{space 2} .0119057{col 41}{space 1}    9.62{col 50}{space 3}0.000{col 58}{space 4} .0912415{col 71}{space 3}  .137911
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0031279{col 30}{space 2}   .00541{col 41}{space 1}    0.58{col 50}{space 3}0.563{col 58}{space 4}-.0074755{col 71}{space 3} .0137312
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0779384{col 30}{space 2} .0604059{col 41}{space 1}   -1.29{col 50}{space 3}0.197{col 58}{space 4}-.1963317{col 71}{space 3} .0404549
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0026738{col 30}{space 2}  .001088{col 41}{space 1}   -2.46{col 50}{space 3}0.014{col 58}{space 4}-.0048063{col 71}{space 3}-.0005413
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1581413{col 30}{space 2}  .036555{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .0864949{col 71}{space 3} .2297877
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3519694{col 30}{space 2} .0334375{col 41}{space 1}   10.53{col 50}{space 3}0.000{col 58}{space 4} .2864331{col 71}{space 3} .4175057
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1113268{col 30}{space 2} .0567111{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0001751{col 71}{space 3} .2224785
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2620793{col 30}{space 2} .0353541{col 41}{space 1}    7.41{col 50}{space 3}0.000{col 58}{space 4} .1927865{col 71}{space 3} .3313721
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5431061{col 30}{space 2} .0500856{col 41}{space 1}   10.84{col 50}{space 3}0.000{col 58}{space 4} .4449402{col 71}{space 3}  .641272
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1424599{col 30}{space 2}  .033568{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .0766679{col 71}{space 3} .2082519
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .240246{col 30}{space 2} .0313548{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .1787917{col 71}{space 3} .3017002
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1159852{col 30}{space 2} .0308391{col 41}{space 1}   -3.76{col 50}{space 3}0.000{col 58}{space 4}-.1764288{col 71}{space 3}-.0555416
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0024041{col 30}{space 2} .0011572{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0001361{col 71}{space 3} .0046721
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0074235{col 30}{space 2} .0261629{col 41}{space 1}   -0.28{col 50}{space 3}0.777{col 58}{space 4}-.0587019{col 71}{space 3} .0438548
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1716726{col 30}{space 2} .0841092{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0068216{col 71}{space 3} .3365236
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .357112{col 30}{space 2}  .060559{col 41}{space 1}    5.90{col 50}{space 3}0.000{col 58}{space 4} .2384184{col 71}{space 3} .4758055
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3992384{col 30}{space 2} .0688818{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .2642326{col 71}{space 3} .5342442
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2080187{col 30}{space 2} .0555036{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0992336{col 71}{space 3} .3168038
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3288408{col 30}{space 2} .0532636{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4}  .224446{col 71}{space 3} .4332357
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.7067797{col 30}{space 2} .1255875{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.9529266{col 71}{space 3}-.4606327
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1015953{col 30}{space 2}  .021069{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .0603007{col 71}{space 3} .1428898
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1751312{col 30}{space 2} .0350255{col 41}{space 1}   -5.00{col 50}{space 3}0.000{col 58}{space 4}-.2437799{col 71}{space 3}-.1064825
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0361557{col 30}{space 2}  .035022{col 41}{space 1}   -1.03{col 50}{space 3}0.302{col 58}{space 4}-.1047975{col 71}{space 3} .0324862
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3474037{col 30}{space 2} .0327382{col 41}{space 1}   10.61{col 50}{space 3}0.000{col 58}{space 4} .2832381{col 71}{space 3} .4115693
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1024657{col 30}{space 2} .0329921{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4} .0378023{col 71}{space 3} .1671291
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2506828{col 30}{space 2} .0321762{col 41}{space 1}    7.79{col 50}{space 3}0.000{col 58}{space 4} .1876186{col 71}{space 3}  .313747
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.787997{col 30}{space 2} .0981898{col 41}{space 1}   38.58{col 50}{space 3}0.000{col 58}{space 4} 3.595549{col 71}{space 3} 3.980446
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76639708
         {txt}sigma_e {c |} {res}  1.243095
             {txt}rho {c |} {res} .27541536{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S12_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S12_farmer_imr.rtf not found)
(output written to {browse  `"S12_farmer_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************  
. *                                 S13_S14                                      *
. ******************************************************************************** 
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(4,932 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    62,289
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    26,569

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0596                                         {txt}min = {res}         1
{txt}     between = {res}0.4347                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.3553                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 27632.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:26,569} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1996823{col 30}{space 2} .0062404{col 41}{space 1}   32.00{col 50}{space 3}0.000{col 58}{space 4} .1874513{col 71}{space 3} .2119132
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0220528{col 30}{space 2} .0021802{col 41}{space 1}   10.11{col 50}{space 3}0.000{col 58}{space 4} .0177796{col 71}{space 3}  .026326
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1307372{col 30}{space 2} .0267708{col 41}{space 1}   -4.88{col 50}{space 3}0.000{col 58}{space 4}-.1832071{col 71}{space 3}-.0782674
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0001199{col 30}{space 2} .0004353{col 41}{space 1}   -0.28{col 50}{space 3}0.783{col 58}{space 4}-.0009731{col 71}{space 3} .0007332
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0161526{col 30}{space 2} .0174564{col 41}{space 1}   -0.93{col 50}{space 3}0.355{col 58}{space 4}-.0503665{col 71}{space 3} .0180614
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1074779{col 30}{space 2} .0135902{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .0808415{col 71}{space 3} .1341142
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0786802{col 30}{space 2} .0286391{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.1348119{col 71}{space 3}-.0225486
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0525039{col 30}{space 2} .0176665{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4} .0178781{col 71}{space 3} .0871297
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1494678{col 30}{space 2} .0328859{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0850127{col 71}{space 3} .2139229
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0082685{col 30}{space 2} .0203042{col 41}{space 1}    0.41{col 50}{space 3}0.684{col 58}{space 4} -.031527{col 71}{space 3}  .048064
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0606845{col 30}{space 2} .0177409{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0259131{col 71}{space 3} .0954559
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1133237{col 30}{space 2} .0172547{col 41}{space 1}   -6.57{col 50}{space 3}0.000{col 58}{space 4}-.1471422{col 71}{space 3}-.0795052
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0058284{col 30}{space 2}  .001093{col 41}{space 1}    5.33{col 50}{space 3}0.000{col 58}{space 4} .0036861{col 71}{space 3} .0079707
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1717338{col 30}{space 2} .0143173{col 41}{space 1}   11.99{col 50}{space 3}0.000{col 58}{space 4} .1436724{col 71}{space 3} .1997952
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .124073{col 30}{space 2} .0349543{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0555639{col 71}{space 3} .1925821
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0073248{col 30}{space 2} .0237695{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.0392625{col 71}{space 3} .0539122
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1594942{col 30}{space 2} .0290557{col 41}{space 1}   -5.49{col 50}{space 3}0.000{col 58}{space 4}-.2164424{col 71}{space 3}-.1025461
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2121453{col 30}{space 2} .0256759{col 41}{space 1}   -8.26{col 50}{space 3}0.000{col 58}{space 4}-.2624691{col 71}{space 3}-.1618214
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3038407{col 30}{space 2} .0226091{col 41}{space 1}  -13.44{col 50}{space 3}0.000{col 58}{space 4}-.3481537{col 71}{space 3}-.2595276
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.4293491{col 30}{space 2} .0602434{col 41}{space 1}   -7.13{col 50}{space 3}0.000{col 58}{space 4}-.5474239{col 71}{space 3}-.3112743
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3055986{col 30}{space 2} .0080747{col 41}{space 1}   37.85{col 50}{space 3}0.000{col 58}{space 4} .2897725{col 71}{space 3} .3214246
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .4563853{col 30}{space 2} .0265766{col 41}{space 1}   17.17{col 50}{space 3}0.000{col 58}{space 4} .4042961{col 71}{space 3} .5084744
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1968701{col 30}{space 2} .0270102{col 41}{space 1}   -7.29{col 50}{space 3}0.000{col 58}{space 4} -.249809{col 71}{space 3}-.1439311
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} 1.140554{col 30}{space 2} .0286279{col 41}{space 1}   39.84{col 50}{space 3}0.000{col 58}{space 4} 1.084444{col 71}{space 3} 1.196664
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .7078639{col 30}{space 2} .0259435{col 41}{space 1}   27.28{col 50}{space 3}0.000{col 58}{space 4} .6570156{col 71}{space 3} .7587121
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .834618{col 30}{space 2} .0321734{col 41}{space 1}   25.94{col 50}{space 3}0.000{col 58}{space 4} .7715593{col 71}{space 3} .8976768
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2585124{col 30}{space 2} .0409558{col 41}{space 1}   -6.31{col 50}{space 3}0.000{col 58}{space 4}-.3387844{col 71}{space 3}-.1782404
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} -.115383{col 30}{space 2}  .030578{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.1753148{col 71}{space 3}-.0554512
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1714854{col 30}{space 2} .0341051{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .1046406{col 71}{space 3} .2383303
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0031203{col 30}{space 2} .0308591{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4} -.063603{col 71}{space 3} .0573623
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0852724{col 30}{space 2} .0351785{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0163238{col 71}{space 3}  .154221
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1879293{col 30}{space 2} .0339099{col 41}{space 1}   -5.54{col 50}{space 3}0.000{col 58}{space 4}-.2543914{col 71}{space 3}-.1214672
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0642687{col 30}{space 2}  .033605{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0015958{col 71}{space 3} .1301333
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.4849725{col 30}{space 2} .0440698{col 41}{space 1}  -11.00{col 50}{space 3}0.000{col 58}{space 4}-.5713476{col 71}{space 3}-.3985973
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2403127{col 30}{space 2} .0381918{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1654582{col 71}{space 3} .3151672
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.2598023{col 30}{space 2} .0373026{col 41}{space 1}   -6.96{col 50}{space 3}0.000{col 58}{space 4}-.3329141{col 71}{space 3}-.1866904
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .0083619{col 30}{space 2} .0513599{col 41}{space 1}    0.16{col 50}{space 3}0.871{col 58}{space 4}-.0923017{col 71}{space 3} .1090254
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .51531593
         {txt}sigma_e {c |} {res} 1.1140151
             {txt}rho {c |} {res} .17626047{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,874
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,641

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0261                                         {txt}min = {res}         1
{txt}     between = {res}0.4309                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3181                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2991.80
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,641} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0670298{col 30}{space 2} .0122852{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .0429513{col 71}{space 3} .0911083
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0340913{col 30}{space 2} .0069743{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4}  .020422{col 71}{space 3} .0477606
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0958377{col 30}{space 2} .0595896{col 41}{space 1}   -1.61{col 50}{space 3}0.108{col 58}{space 4} -.212631{col 71}{space 3} .0209557
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0011812{col 30}{space 2} .0010049{col 41}{space 1}    1.18{col 50}{space 3}0.240{col 58}{space 4}-.0007884{col 71}{space 3} .0031508
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0694823{col 30}{space 2} .0390069{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.1459343{col 71}{space 3} .0069698
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1049532{col 30}{space 2}   .03102{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4}  .044155{col 71}{space 3} .1657513
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2601269{col 30}{space 2} .1796791{col 41}{space 1}   -1.45{col 50}{space 3}0.148{col 58}{space 4}-.6122914{col 71}{space 3} .0920375
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0534267{col 30}{space 2} .0404689{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-.0258909{col 71}{space 3} .1327443
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0905999{col 30}{space 2} .0642626{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4}-.2165522{col 71}{space 3} .0353524
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .055284{col 30}{space 2}  .074991{col 41}{space 1}    0.74{col 50}{space 3}0.461{col 58}{space 4}-.0916956{col 71}{space 3} .2022636
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  -.00566{col 30}{space 2} .0554945{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.1144272{col 71}{space 3} .1031072
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2068014{col 30}{space 2} .0390181{col 41}{space 1}   -5.30{col 50}{space 3}0.000{col 58}{space 4}-.2832756{col 71}{space 3}-.1303273
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0181962{col 30}{space 2} .0064088{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0056351{col 71}{space 3} .0307573
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0141887{col 30}{space 2} .0278444{col 41}{space 1}   -0.51{col 50}{space 3}0.610{col 58}{space 4}-.0687628{col 71}{space 3} .0403855
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2744537{col 30}{space 2} .2713482{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4} -.257379{col 71}{space 3} .8062864
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0890203{col 30}{space 2} .0546886{col 41}{space 1}   -1.63{col 50}{space 3}0.104{col 58}{space 4} -.196208{col 71}{space 3} .0181673
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2376929{col 30}{space 2} .0634276{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.3620086{col 71}{space 3}-.1133771
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3397674{col 30}{space 2}  .099397{col 41}{space 1}   -3.42{col 50}{space 3}0.001{col 58}{space 4} -.534582{col 71}{space 3}-.1449528
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2425953{col 30}{space 2} .0654327{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.3708409{col 71}{space 3}-.1143496
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.2284876{col 30}{space 2} .1367398{col 41}{space 1}   -1.67{col 50}{space 3}0.095{col 58}{space 4}-.4964927{col 71}{space 3} .0395175
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2806838{col 30}{space 2} .0154692{col 41}{space 1}   18.14{col 50}{space 3}0.000{col 58}{space 4} .2503647{col 71}{space 3} .3110029
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1630279{col 30}{space 2} .0217227{col 41}{space 1}   -7.50{col 50}{space 3}0.000{col 58}{space 4}-.2056037{col 71}{space 3}-.1204521
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5938696{col 30}{space 2} .0839388{col 41}{space 1}    7.08{col 50}{space 3}0.000{col 58}{space 4} .4293526{col 71}{space 3} .7583866
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55350399
         {txt}sigma_e {c |} {res} .88402885
             {txt}rho {c |} {res} .28161971{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,351
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1482                                         {txt}min = {res}         1
{txt}     between = {res}0.3722                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.3090                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2918.47
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2754946{col 30}{space 2}  .015461{col 41}{space 1}   17.82{col 50}{space 3}0.000{col 58}{space 4} .2451915{col 71}{space 3} .3057977
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0043887{col 30}{space 2} .0082476{col 41}{space 1}   -0.53{col 50}{space 3}0.595{col 58}{space 4}-.0205537{col 71}{space 3} .0117764
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1887521{col 30}{space 2} .0755647{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.3368562{col 71}{space 3}-.0406479
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0017066{col 30}{space 2} .0012605{col 41}{space 1}    1.35{col 50}{space 3}0.176{col 58}{space 4}-.0007639{col 71}{space 3} .0041771
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0008799{col 30}{space 2} .0460003{col 41}{space 1}   -0.02{col 50}{space 3}0.985{col 58}{space 4}-.0910389{col 71}{space 3} .0892791
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1035238{col 30}{space 2} .0399849{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0251548{col 71}{space 3} .1818928
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1869907{col 30}{space 2} .1516901{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.1103165{col 71}{space 3} .4842979
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0670874{col 30}{space 2} .0498504{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4}-.0306177{col 71}{space 3} .1647924
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0863858{col 30}{space 2} .1406161{col 41}{space 1}    0.61{col 50}{space 3}0.539{col 58}{space 4}-.1892167{col 71}{space 3} .3619883
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0078121{col 30}{space 2} .0634539{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4}-.1165552{col 71}{space 3} .1321794
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1150691{col 30}{space 2} .0462974{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .0243278{col 71}{space 3} .2058103
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2455873{col 30}{space 2} .0469143{col 41}{space 1}   -5.23{col 50}{space 3}0.000{col 58}{space 4}-.3375376{col 71}{space 3}-.1536369
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1458373{col 30}{space 2} .0294298{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0881558{col 71}{space 3} .2035187
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1605165{col 30}{space 2} .0428014{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0766273{col 71}{space 3} .2444056
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1516702{col 30}{space 2} .1981366{col 41}{space 1}   -0.77{col 50}{space 3}0.444{col 58}{space 4}-.5400109{col 71}{space 3} .2366705
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0564577{col 30}{space 2} .0692196{col 41}{space 1}   -0.82{col 50}{space 3}0.415{col 58}{space 4}-.1921255{col 71}{space 3} .0792102
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0229293{col 30}{space 2} .1316412{col 41}{space 1}    0.17{col 50}{space 3}0.862{col 58}{space 4}-.2350827{col 71}{space 3} .2809414
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0446743{col 30}{space 2} .0796441{col 41}{space 1}   -0.56{col 50}{space 3}0.575{col 58}{space 4}-.2007739{col 71}{space 3} .1114253
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2506454{col 30}{space 2} .0647598{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.3775723{col 71}{space 3}-.1237185
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.6569271{col 30}{space 2} .1843226{col 41}{space 1}   -3.56{col 50}{space 3}0.000{col 58}{space 4}-1.018193{col 71}{space 3}-.2956615
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3105857{col 30}{space 2} .0230444{col 41}{space 1}   13.48{col 50}{space 3}0.000{col 58}{space 4} .2654194{col 71}{space 3}  .355752
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .7715898{col 30}{space 2} .0449424{col 41}{space 1}   17.17{col 50}{space 3}0.000{col 58}{space 4} .6835044{col 71}{space 3} .8596752
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3989293{col 30}{space 2}  .036528{col 41}{space 1}   10.92{col 50}{space 3}0.000{col 58}{space 4} .3273358{col 71}{space 3} .4705229
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .2047988{col 30}{space 2} .1057645{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0024958{col 71}{space 3} .4120934
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .52231725
         {txt}sigma_e {c |} {res} 1.1469682
             {txt}rho {c |} {res} .17176004{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,310
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,178

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1935                                         {txt}min = {res}         1
{txt}     between = {res}0.3305                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2862                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2386.78
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,178} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2298401{col 30}{space 2} .0268991{col 41}{space 1}    8.54{col 50}{space 3}0.000{col 58}{space 4} .1771187{col 71}{space 3} .2825615
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .001111{col 30}{space 2}  .004473{col 41}{space 1}    0.25{col 50}{space 3}0.804{col 58}{space 4}-.0076559{col 71}{space 3} .0098779
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.047659{col 30}{space 2} .0783228{col 41}{space 1}   -0.61{col 50}{space 3}0.543{col 58}{space 4}-.2011688{col 71}{space 3} .1058509
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025923{col 30}{space 2} .0012203{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.0049841{col 71}{space 3}-.0002005
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1252286{col 30}{space 2} .0474215{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4} -.218173{col 71}{space 3}-.0322843
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0941284{col 30}{space 2} .0368177{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4}  .021967{col 71}{space 3} .1662898
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0267691{col 30}{space 2} .0820551{col 41}{space 1}   -0.33{col 50}{space 3}0.744{col 58}{space 4}-.1875942{col 71}{space 3}  .134056
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.1089205{col 30}{space 2} .0517196{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4} -.210289{col 71}{space 3}-.0075519
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1387372{col 30}{space 2} .1193838{col 41}{space 1}    1.16{col 50}{space 3}0.245{col 58}{space 4}-.0952509{col 71}{space 3} .3727252
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1587624{col 30}{space 2} .0713869{col 41}{space 1}    2.22{col 50}{space 3}0.026{col 58}{space 4} .0188467{col 71}{space 3} .2986782
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .003271{col 30}{space 2} .0485063{col 41}{space 1}    0.07{col 50}{space 3}0.946{col 58}{space 4}-.0917997{col 71}{space 3} .0983417
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0526286{col 30}{space 2}  .045982{col 41}{space 1}   -1.14{col 50}{space 3}0.252{col 58}{space 4}-.1427516{col 71}{space 3} .0374944
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0007214{col 30}{space 2} .0011024{col 41}{space 1}    0.65{col 50}{space 3}0.513{col 58}{space 4}-.0014392{col 71}{space 3}  .002882
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3626514{col 30}{space 2} .1476494{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0732639{col 71}{space 3} .6520389
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0481372{col 30}{space 2} .0900861{col 41}{space 1}   -0.53{col 50}{space 3}0.593{col 58}{space 4}-.2247027{col 71}{space 3} .1284283
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0542026{col 30}{space 2} .0604406{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.1726641{col 71}{space 3} .0642589
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3516631{col 30}{space 2} .0999873{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}-.5476345{col 71}{space 3}-.1556916
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2194223{col 30}{space 2} .0749675{col 41}{space 1}   -2.93{col 50}{space 3}0.003{col 58}{space 4}-.3663558{col 71}{space 3}-.0724887
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0914193{col 30}{space 2} .0577911{col 41}{space 1}   -1.58{col 50}{space 3}0.114{col 58}{space 4}-.2046879{col 71}{space 3} .0218492
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -.238527{col 30}{space 2} .1855639{col 41}{space 1}   -1.29{col 50}{space 3}0.199{col 58}{space 4}-.6022255{col 71}{space 3} .1251716
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .240523{col 30}{space 2}  .029957{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .1818083{col 71}{space 3} .2992377
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .4159631{col 30}{space 2} .0271874{col 41}{space 1}   15.30{col 50}{space 3}0.000{col 58}{space 4} .3626768{col 71}{space 3} .4692494
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0932574{col 30}{space 2} .1066161{col 41}{space 1}    0.87{col 50}{space 3}0.382{col 58}{space 4}-.1157063{col 71}{space 3} .3022211
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .25155945
         {txt}sigma_e {c |} {res} .86587925
             {txt}rho {c |} {res} .07783505{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,811
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,302

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0736                                         {txt}min = {res}         1
{txt}     between = {res}0.1761                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1444                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1728.21
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,302} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1823342{col 30}{space 2} .0160141{col 41}{space 1}   11.39{col 50}{space 3}0.000{col 58}{space 4} .1509471{col 71}{space 3} .2137213
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0092265{col 30}{space 2} .0036722{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0020292{col 71}{space 3} .0164238
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0563952{col 30}{space 2} .0549629{col 41}{space 1}   -1.03{col 50}{space 3}0.305{col 58}{space 4}-.1641204{col 71}{space 3}   .05133
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0001664{col 30}{space 2} .0009241{col 41}{space 1}    0.18{col 50}{space 3}0.857{col 58}{space 4}-.0016449{col 71}{space 3} .0019777
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0744605{col 30}{space 2} .0420429{col 41}{space 1}   -1.77{col 50}{space 3}0.077{col 58}{space 4}-.1568631{col 71}{space 3} .0079421
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0251634{col 30}{space 2} .0258233{col 41}{space 1}   -0.97{col 50}{space 3}0.330{col 58}{space 4}-.0757762{col 71}{space 3} .0254494
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0968782{col 30}{space 2} .0406522{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4} -.176555{col 71}{space 3}-.0172015
{txt}{space 11}phone {c |}{col 18}{res}{space 2}   .07211{col 30}{space 2} .0343321{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0048204{col 71}{space 3} .1393997
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0314126{col 30}{space 2} .0735169{col 41}{space 1}    0.43{col 50}{space 3}0.669{col 58}{space 4}-.1126779{col 71}{space 3} .1755032
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0674517{col 30}{space 2} .0585183{col 41}{space 1}    1.15{col 50}{space 3}0.249{col 58}{space 4}-.0472419{col 71}{space 3} .1821454
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0689574{col 30}{space 2} .0408203{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4} -.011049{col 71}{space 3} .1489637
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0727368{col 30}{space 2} .0464011{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0182076{col 71}{space 3} .1636813
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0136561{col 30}{space 2} .0072485{col 41}{space 1}    1.88{col 50}{space 3}0.060{col 58}{space 4}-.0005506{col 71}{space 3} .0278629
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1173507{col 30}{space 2} .0453621{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0284426{col 71}{space 3} .2062587
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2391371{col 30}{space 2} .0459833{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .1490115{col 71}{space 3} .3292626
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0722408{col 30}{space 2} .0478416{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4} -.021527{col 71}{space 3} .1660087
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3006591{col 30}{space 2} .0551938{col 41}{space 1}   -5.45{col 50}{space 3}0.000{col 58}{space 4} -.408837{col 71}{space 3}-.1924813
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2656003{col 30}{space 2} .0640225{col 41}{space 1}   -4.15{col 50}{space 3}0.000{col 58}{space 4}-.3910822{col 71}{space 3}-.1401185
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2438707{col 30}{space 2} .0477944{col 41}{space 1}   -5.10{col 50}{space 3}0.000{col 58}{space 4} -.337546{col 71}{space 3}-.1501955
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.0368567{col 30}{space 2} .1277635{col 41}{space 1}   -0.29{col 50}{space 3}0.773{col 58}{space 4}-.2872685{col 71}{space 3} .2135551
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1538104{col 30}{space 2} .0198525{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .1149003{col 71}{space 3} .1927206
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6149049{col 30}{space 2} .0439715{col 41}{space 1}  -13.98{col 50}{space 3}0.000{col 58}{space 4}-.7010875{col 71}{space 3}-.5287223
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.3060913{col 30}{space 2}  .041484{col 41}{space 1}   -7.38{col 50}{space 3}0.000{col 58}{space 4}-.3873984{col 71}{space 3}-.2247842
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3471413{col 30}{space 2} .0402144{col 41}{space 1}   -8.63{col 50}{space 3}0.000{col 58}{space 4}-.4259601{col 71}{space 3}-.2683225
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.164277{col 30}{space 2} .0695328{col 41}{space 1}   16.74{col 50}{space 3}0.000{col 58}{space 4} 1.027995{col 71}{space 3} 1.300558
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .58631561
         {txt}sigma_e {c |} {res} .98177213
             {txt}rho {c |} {res} .26288989{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,194
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0908                                         {txt}min = {res}         1
{txt}     between = {res}0.4419                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.3668                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  6406.80
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3047608{col 30}{space 2} .0145692{col 41}{space 1}   20.92{col 50}{space 3}0.000{col 58}{space 4} .2762057{col 71}{space 3}  .333316
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0298334{col 30}{space 2} .0050546{col 41}{space 1}    5.90{col 50}{space 3}0.000{col 58}{space 4} .0199266{col 71}{space 3} .0397402
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0207603{col 30}{space 2} .0630235{col 41}{space 1}   -0.33{col 50}{space 3}0.742{col 58}{space 4}-.1442841{col 71}{space 3} .1027636
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0018223{col 30}{space 2} .0010449{col 41}{space 1}   -1.74{col 50}{space 3}0.081{col 58}{space 4}-.0038704{col 71}{space 3} .0002257
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1084667{col 30}{space 2} .0401996{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4}-.1872564{col 71}{space 3}-.0296769
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0309672{col 30}{space 2}   .03264{col 41}{space 1}    0.95{col 50}{space 3}0.343{col 58}{space 4} -.033006{col 71}{space 3} .0949405
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1453309{col 30}{space 2} .0893962{col 41}{space 1}    1.63{col 50}{space 3}0.104{col 58}{space 4}-.0298824{col 71}{space 3} .3205442
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0624115{col 30}{space 2} .0453509{col 41}{space 1}   -1.38{col 50}{space 3}0.169{col 58}{space 4}-.1512976{col 71}{space 3} .0264746
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2294068{col 30}{space 2} .0837652{col 41}{space 1}   -2.74{col 50}{space 3}0.006{col 58}{space 4}-.3935836{col 71}{space 3}  -.06523
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0319077{col 30}{space 2} .0429397{col 41}{space 1}   -0.74{col 50}{space 3}0.457{col 58}{space 4} -.116068{col 71}{space 3} .0522527
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0290678{col 30}{space 2}  .040402{col 41}{space 1}    0.72{col 50}{space 3}0.472{col 58}{space 4}-.0501187{col 71}{space 3} .1082543
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0492789{col 30}{space 2} .0468438{col 41}{space 1}   -1.05{col 50}{space 3}0.293{col 58}{space 4}-.1410911{col 71}{space 3} .0425332
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0159006{col 30}{space 2} .0047073{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0066745{col 71}{space 3} .0251267
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}   .21852{col 30}{space 2} .0294621{col 41}{space 1}    7.42{col 50}{space 3}0.000{col 58}{space 4} .1607754{col 71}{space 3} .2762646
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0107984{col 30}{space 2} .1062124{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.2189708{col 71}{space 3}  .197374
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} -.102685{col 30}{space 2} .0575275{col 41}{space 1}   -1.78{col 50}{space 3}0.074{col 58}{space 4} -.215437{col 71}{space 3} .0100669
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0538788{col 30}{space 2} .0794742{col 41}{space 1}   -0.68{col 50}{space 3}0.498{col 58}{space 4}-.2096454{col 71}{space 3} .1018878
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2646555{col 30}{space 2} .0485239{col 41}{space 1}   -5.45{col 50}{space 3}0.000{col 58}{space 4}-.3597606{col 71}{space 3}-.1695504
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3510572{col 30}{space 2} .0507069{col 41}{space 1}   -6.92{col 50}{space 3}0.000{col 58}{space 4}-.4504409{col 71}{space 3}-.2516735
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .1293024{col 30}{space 2} .1397567{col 41}{space 1}    0.93{col 50}{space 3}0.355{col 58}{space 4}-.1446156{col 71}{space 3} .4032204
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2565197{col 30}{space 2} .0174494{col 41}{space 1}   14.70{col 50}{space 3}0.000{col 58}{space 4} .2223195{col 71}{space 3} .2907199
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0481037{col 30}{space 2} .0343433{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4} -.019208{col 71}{space 3} .1154155
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  .031426{col 30}{space 2} .0278354{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0231305{col 71}{space 3} .0859824
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0049692{col 30}{space 2} .0354537{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4}-.0744572{col 71}{space 3} .0645188
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4628823{col 30}{space 2} .0855573{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .2951931{col 71}{space 3} .6305716
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .61254894
         {txt}sigma_e {c |} {res}  1.135726
             {txt}rho {c |} {res} .22534294{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,749
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,278

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0536                                         {txt}min = {res}         1
{txt}     between = {res}0.4520                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.2753                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  4823.28
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,278} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1879532{col 30}{space 2} .0118692{col 41}{space 1}   15.84{col 50}{space 3}0.000{col 58}{space 4} .1646899{col 71}{space 3} .2112164
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0345071{col 30}{space 2} .0050816{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .0245474{col 71}{space 3} .0444668
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1305425{col 30}{space 2} .0569516{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.2421656{col 71}{space 3}-.0189194
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0003133{col 30}{space 2}  .000972{col 41}{space 1}    0.32{col 50}{space 3}0.747{col 58}{space 4}-.0015917{col 71}{space 3} .0022184
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0775956{col 30}{space 2} .0336335{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0116751{col 71}{space 3} .1435161
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2249296{col 30}{space 2} .0309639{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .1642415{col 71}{space 3} .2856178
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0804751{col 30}{space 2} .0590648{col 41}{space 1}   -1.36{col 50}{space 3}0.173{col 58}{space 4}-.1962399{col 71}{space 3} .0352898
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1322215{col 30}{space 2} .0341201{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0653473{col 71}{space 3} .1990956
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2779999{col 30}{space 2} .0487403{col 41}{space 1}    5.70{col 50}{space 3}0.000{col 58}{space 4} .1824706{col 71}{space 3} .3735292
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.061657{col 30}{space 2} .0318451{col 41}{space 1}   -1.94{col 50}{space 3}0.053{col 58}{space 4}-.1240723{col 71}{space 3} .0007583
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0492128{col 30}{space 2} .0325536{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0145911{col 71}{space 3} .1130167
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1475544{col 30}{space 2} .0302425{col 41}{space 1}   -4.88{col 50}{space 3}0.000{col 58}{space 4}-.2068286{col 71}{space 3}-.0882801
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0043326{col 30}{space 2} .0019914{col 41}{space 1}    2.18{col 50}{space 3}0.030{col 58}{space 4} .0004296{col 71}{space 3} .0082356
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1927513{col 30}{space 2} .0252749{col 41}{space 1}    7.63{col 50}{space 3}0.000{col 58}{space 4} .1432135{col 71}{space 3} .2422892
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0189696{col 30}{space 2} .0828021{col 41}{space 1}    0.23{col 50}{space 3}0.819{col 58}{space 4}-.1433196{col 71}{space 3} .1812588
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0175245{col 30}{space 2} .0568481{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.0938957{col 71}{space 3} .1289447
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0026037{col 30}{space 2}  .064514{col 41}{space 1}    0.04{col 50}{space 3}0.968{col 58}{space 4}-.1238415{col 71}{space 3} .1290489
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2247937{col 30}{space 2} .0500063{col 41}{space 1}   -4.50{col 50}{space 3}0.000{col 58}{space 4}-.3228042{col 71}{space 3}-.1267832
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3847117{col 30}{space 2} .0503536{col 41}{space 1}   -7.64{col 50}{space 3}0.000{col 58}{space 4}-.4834029{col 71}{space 3}-.2860205
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.6627557{col 30}{space 2} .1228814{col 41}{space 1}   -5.39{col 50}{space 3}0.000{col 58}{space 4}-.9035989{col 71}{space 3}-.4219126
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .5170574{col 30}{space 2} .0193652{col 41}{space 1}   26.70{col 50}{space 3}0.000{col 58}{space 4} .4791023{col 71}{space 3} .5550125
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0900806{col 30}{space 2} .0331548{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-.1550627{col 71}{space 3}-.0250984
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .191487{col 30}{space 2} .0348909{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .1231021{col 71}{space 3}  .259872
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .4506727{col 30}{space 2} .0320369{col 41}{space 1}   14.07{col 50}{space 3}0.000{col 58}{space 4} .3878815{col 71}{space 3} .5134639
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2641824{col 30}{space 2} .0313203{col 41}{space 1}    8.43{col 50}{space 3}0.000{col 58}{space 4} .2027958{col 71}{space 3} .3255691
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2930184{col 30}{space 2} .0321105{col 41}{space 1}    9.13{col 50}{space 3}0.000{col 58}{space 4}  .230083{col 71}{space 3} .3559537
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0771152{col 30}{space 2} .0871967{col 41}{space 1}    0.88{col 50}{space 3}0.376{col 58}{space 4}-.0937872{col 71}{space 3} .2480175
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .62086727
         {txt}sigma_e {c |} {res} 1.2249464
             {txt}rho {c |} {res} .20439148{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S13_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S13_farmer_imr.rtf not found)
(output written to {browse  `"S13_farmer_imr.rtf"'})

{com}. 
. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    62,289
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    26,569

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0289                                         {txt}min = {res}         1
{txt}     between = {res}0.4325                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.3404                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 26059.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:26,569} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0251138{col 30}{space 2} .0073169{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4}  .010773{col 71}{space 3} .0394546
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0131824{col 30}{space 2} .0030705{col 41}{space 1}   -4.29{col 50}{space 3}0.000{col 58}{space 4}-.0192004{col 71}{space 3}-.0071644
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0168313{col 30}{space 2} .0369924{col 41}{space 1}   -0.45{col 50}{space 3}0.649{col 58}{space 4} -.089335{col 71}{space 3} .0556724
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0017102{col 30}{space 2} .0006268{col 41}{space 1}   -2.73{col 50}{space 3}0.006{col 58}{space 4}-.0029387{col 71}{space 3}-.0004817
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0309433{col 30}{space 2} .0242366{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0784461{col 71}{space 3} .0165596
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2584219{col 30}{space 2}  .018214{col 41}{space 1}   14.19{col 50}{space 3}0.000{col 58}{space 4}  .222723{col 71}{space 3} .2941207
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1689717{col 30}{space 2}  .036888{col 41}{space 1}    4.58{col 50}{space 3}0.000{col 58}{space 4} .0966726{col 71}{space 3} .2412709
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .207194{col 30}{space 2} .0226429{col 41}{space 1}    9.15{col 50}{space 3}0.000{col 58}{space 4} .1628147{col 71}{space 3} .2515733
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1231462{col 30}{space 2} .0416671{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0414801{col 71}{space 3} .2048122
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1550416{col 30}{space 2} .0253979{col 41}{space 1}    6.10{col 50}{space 3}0.000{col 58}{space 4} .1052626{col 71}{space 3} .2048206
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2317927{col 30}{space 2} .0218311{col 41}{space 1}   10.62{col 50}{space 3}0.000{col 58}{space 4} .1890046{col 71}{space 3} .2745808
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0527542{col 30}{space 2} .0222829{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0090806{col 71}{space 3} .0964278
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0013169{col 30}{space 2} .0012437{col 41}{space 1}   -1.06{col 50}{space 3}0.290{col 58}{space 4}-.0037546{col 71}{space 3} .0011207
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0298279{col 30}{space 2} .0184797{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-.0660474{col 71}{space 3} .0063917
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0563039{col 30}{space 2} .0473501{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0365006{col 71}{space 3} .1491085
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6302998{col 30}{space 2} .0323638{col 41}{space 1}   19.48{col 50}{space 3}0.000{col 58}{space 4}  .566868{col 71}{space 3} .6937317
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7943652{col 30}{space 2} .0384954{col 41}{space 1}   20.64{col 50}{space 3}0.000{col 58}{space 4} .7189156{col 71}{space 3} .8698149
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3634739{col 30}{space 2} .0352476{col 41}{space 1}   10.31{col 50}{space 3}0.000{col 58}{space 4} .2943898{col 71}{space 3} .4325579
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5259293{col 30}{space 2} .0304353{col 41}{space 1}   17.28{col 50}{space 3}0.000{col 58}{space 4} .4662772{col 71}{space 3} .5855814
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4219375{col 30}{space 2} .0800743{col 41}{space 1}    5.27{col 50}{space 3}0.000{col 58}{space 4} .2649947{col 71}{space 3} .5788803
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1907625{col 30}{space 2} .0104061{col 41}{space 1}  -18.33{col 50}{space 3}0.000{col 58}{space 4}-.2111581{col 71}{space 3}-.1703669
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.8273396{col 30}{space 2} .0398436{col 41}{space 1}  -20.76{col 50}{space 3}0.000{col 58}{space 4}-.9054316{col 71}{space 3}-.7492476
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-2.094561{col 30}{space 2} .0401397{col 41}{space 1}  -52.18{col 50}{space 3}0.000{col 58}{space 4}-2.173234{col 71}{space 3}-2.015889
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.536753{col 30}{space 2}  .041591{col 41}{space 1}  -36.95{col 50}{space 3}0.000{col 58}{space 4} -1.61827{col 71}{space 3}-1.455236
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-1.123732{col 30}{space 2} .0401685{col 41}{space 1}  -27.98{col 50}{space 3}0.000{col 58}{space 4}-1.202461{col 71}{space 3}-1.045003
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} -.445923{col 30}{space 2} .0475752{col 41}{space 1}   -9.37{col 50}{space 3}0.000{col 58}{space 4}-.5391687{col 71}{space 3}-.3526774
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1393652{col 30}{space 2} .0481222{col 41}{space 1}   -2.90{col 50}{space 3}0.004{col 58}{space 4}-.2336831{col 71}{space 3}-.0450473
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0590766{col 30}{space 2} .0353484{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4} -.010205{col 71}{space 3} .1283582
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} -.062832{col 30}{space 2}  .041525{col 41}{space 1}   -1.51{col 50}{space 3}0.130{col 58}{space 4}-.1442195{col 71}{space 3} .0185556
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0132389{col 30}{space 2} .0361697{col 41}{space 1}    0.37{col 50}{space 3}0.714{col 58}{space 4}-.0576525{col 71}{space 3} .0841303
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1791572{col 30}{space 2} .0418545{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0971238{col 71}{space 3} .2611906
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0329544{col 30}{space 2} .0430448{col 41}{space 1}   -0.77{col 50}{space 3}0.444{col 58}{space 4}-.1173207{col 71}{space 3} .0514118
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2721422{col 30}{space 2} .0404644{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1928335{col 71}{space 3}  .351451
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .2488531{col 30}{space 2} .0560092{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .1390771{col 71}{space 3} .3586291
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3995041{col 30}{space 2} .0465543{col 41}{space 1}    8.58{col 50}{space 3}0.000{col 58}{space 4} .3082593{col 71}{space 3} .4907489
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .3456839{col 30}{space 2} .0453713{col 41}{space 1}    7.62{col 50}{space 3}0.000{col 58}{space 4} .2567577{col 71}{space 3} .4346101
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.266443{col 30}{space 2} .0702188{col 41}{space 1}   60.76{col 50}{space 3}0.000{col 58}{space 4} 4.128816{col 71}{space 3} 4.404069
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0088509
         {txt}sigma_e {c |} {res} 1.3813944
             {txt}rho {c |} {res} .34783645{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,874
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,641

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0321                                         {txt}min = {res}         1
{txt}     between = {res}0.3889                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.2920                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2333.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,641} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0317359{col 30}{space 2}  .014144{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0040141{col 71}{space 3} .0594576
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0059709{col 30}{space 2} .0090877{col 41}{space 1}    0.66{col 50}{space 3}0.511{col 58}{space 4}-.0118406{col 71}{space 3} .0237825
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0499665{col 30}{space 2} .0819225{col 41}{space 1}    0.61{col 50}{space 3}0.542{col 58}{space 4}-.1105987{col 71}{space 3} .2105317
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0042801{col 30}{space 2} .0013901{col 41}{space 1}   -3.08{col 50}{space 3}0.002{col 58}{space 4}-.0070046{col 71}{space 3}-.0015556
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .048398{col 30}{space 2} .0526926{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0548776{col 71}{space 3} .1516737
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2446149{col 30}{space 2} .0410401{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .1641778{col 71}{space 3}  .325052
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1164679{col 30}{space 2} .1996983{col 41}{space 1}    0.58{col 50}{space 3}0.560{col 58}{space 4}-.2749336{col 71}{space 3} .5078694
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1945824{col 30}{space 2} .0487637{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .0990073{col 71}{space 3} .2901575
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4183513{col 30}{space 2} .0838749{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .2539596{col 71}{space 3} .5827431
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1120533{col 30}{space 2} .0970036{col 41}{space 1}    1.16{col 50}{space 3}0.248{col 58}{space 4}-.0780703{col 71}{space 3} .3021769
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2029606{col 30}{space 2} .0682514{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4} .0691904{col 71}{space 3} .3367309
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.090116{col 30}{space 2} .0497956{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4}-.1877137{col 71}{space 3} .0074816
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0094491{col 30}{space 2} .0056385{col 41}{space 1}   -1.68{col 50}{space 3}0.094{col 58}{space 4}-.0205004{col 71}{space 3} .0016022
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2377815{col 30}{space 2} .0372193{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .1648329{col 71}{space 3}   .31073
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2154256{col 30}{space 2} .3162972{col 41}{space 1}    0.68{col 50}{space 3}0.496{col 58}{space 4}-.4045056{col 71}{space 3} .8353567
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .54693{col 30}{space 2} .0713925{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .4070034{col 71}{space 3} .6868567
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6147428{col 30}{space 2} .0858445{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .4464907{col 71}{space 3}  .782995
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6889993{col 30}{space 2} .1346219{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .4251452{col 71}{space 3} .9528534
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5420593{col 30}{space 2}  .084008{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .3774067{col 71}{space 3}  .706712
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .0725709{col 30}{space 2} .1938778{col 41}{space 1}    0.37{col 50}{space 3}0.708{col 58}{space 4}-.3074226{col 71}{space 3} .4525643
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1106633{col 30}{space 2} .0196436{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.1491641{col 71}{space 3}-.0721625
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1918543{col 30}{space 2} .0274408{col 41}{space 1}   -6.99{col 50}{space 3}0.000{col 58}{space 4}-.2456373{col 71}{space 3}-.1380713
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.050713{col 30}{space 2} .1203962{col 41}{space 1}   17.03{col 50}{space 3}0.000{col 58}{space 4} 1.814741{col 71}{space 3} 2.286686
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86384586
         {txt}sigma_e {c |} {res} 1.0671941
             {txt}rho {c |} {res}  .3958499{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,351
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,890

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0465                                         {txt}min = {res}         1
{txt}     between = {res}0.4495                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.3553                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3277.60
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:2,890} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0012312{col 30}{space 2}  .019471{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.0369313{col 71}{space 3} .0393937
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0096636{col 30}{space 2} .0111712{col 41}{space 1}    0.87{col 50}{space 3}0.387{col 58}{space 4}-.0122316{col 71}{space 3} .0315589
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3731899{col 30}{space 2} .1041884{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-.5773955{col 71}{space 3}-.1689844
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0088957{col 30}{space 2}  .001818{col 41}{space 1}   -4.89{col 50}{space 3}0.000{col 58}{space 4}-.0124589{col 71}{space 3}-.0053326
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0971255{col 30}{space 2}  .065138{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-.2247935{col 71}{space 3} .0305426
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2717813{col 30}{space 2}  .056309{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .1614178{col 71}{space 3} .3821449
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3552843{col 30}{space 2}  .166497{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0289561{col 71}{space 3} .6816125
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4186289{col 30}{space 2} .0684525{col 41}{space 1}    6.12{col 50}{space 3}0.000{col 58}{space 4} .2844644{col 71}{space 3} .5527934
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6466754{col 30}{space 2} .1778859{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .2980255{col 71}{space 3} .9953253
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2885934{col 30}{space 2} .0844118{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .1231493{col 71}{space 3} .4540374
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3748776{col 30}{space 2} .0582849{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .2606413{col 71}{space 3}  .489114
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1100214{col 30}{space 2} .0623896{col 41}{space 1}   -1.76{col 50}{space 3}0.078{col 58}{space 4}-.2323027{col 71}{space 3}   .01226
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0045604{col 30}{space 2} .0301798{col 41}{space 1}   -0.15{col 50}{space 3}0.880{col 58}{space 4}-.0637117{col 71}{space 3} .0545909
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0078477{col 30}{space 2} .0575462{col 41}{space 1}   -0.14{col 50}{space 3}0.892{col 58}{space 4}-.1206361{col 71}{space 3} .1049408
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1528269{col 30}{space 2} .2542629{col 41}{space 1}    0.60{col 50}{space 3}0.548{col 58}{space 4}-.3455193{col 71}{space 3} .6511731
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5931285{col 30}{space 2} .1008205{col 41}{space 1}    5.88{col 50}{space 3}0.000{col 58}{space 4}  .395524{col 71}{space 3} .7907331
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.015976{col 30}{space 2} .1748502{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4}  .673276{col 71}{space 3} 1.358676
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .6648058{col 30}{space 2} .1110113{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .4472276{col 71}{space 3}  .882384
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7272937{col 30}{space 2} .0926457{col 41}{space 1}    7.85{col 50}{space 3}0.000{col 58}{space 4} .5457114{col 71}{space 3} .9088759
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.0890532{col 30}{space 2} .2549033{col 41}{space 1}   -0.35{col 50}{space 3}0.727{col 58}{space 4}-.5886545{col 71}{space 3} .4105481
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.199363{col 30}{space 2} .0324027{col 41}{space 1}   -6.15{col 50}{space 3}0.000{col 58}{space 4}-.2628711{col 71}{space 3} -.135855
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2825578{col 30}{space 2}  .060079{col 41}{space 1}   -4.70{col 50}{space 3}0.000{col 58}{space 4}-.4003105{col 71}{space 3}-.1648051
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0190535{col 30}{space 2} .0491323{col 41}{space 1}   -0.39{col 50}{space 3}0.698{col 58}{space 4} -.115351{col 71}{space 3} .0772441
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.375673{col 30}{space 2} .1542436{col 41}{space 1}   28.37{col 50}{space 3}0.000{col 58}{space 4} 4.073361{col 71}{space 3} 4.677985
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .98771852
         {txt}sigma_e {c |} {res} 1.5003933
             {txt}rho {c |} {res} .30234213{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,310
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,178

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0282                                         {txt}min = {res}         1
{txt}     between = {res}0.2285                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1637                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1251.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,178} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2638197{col 30}{space 2} .0438494{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4} .1778765{col 71}{space 3} .3497629
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0092492{col 30}{space 2} .0082708{col 41}{space 1}    1.12{col 50}{space 3}0.263{col 58}{space 4}-.0069613{col 71}{space 3} .0254597
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0218122{col 30}{space 2} .1487217{col 41}{space 1}   -0.15{col 50}{space 3}0.883{col 58}{space 4}-.3133013{col 71}{space 3}  .269677
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0035389{col 30}{space 2}  .002182{col 41}{space 1}    1.62{col 50}{space 3}0.105{col 58}{space 4}-.0007379{col 71}{space 3} .0078156
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0191218{col 30}{space 2} .0960819{col 41}{space 1}    0.20{col 50}{space 3}0.842{col 58}{space 4}-.1691954{col 71}{space 3} .2074389
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .276985{col 30}{space 2} .0645494{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .1504706{col 71}{space 3} .4034995
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3863036{col 30}{space 2} .1600409{col 41}{space 1}    2.41{col 50}{space 3}0.016{col 58}{space 4} .0726292{col 71}{space 3}  .699978
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0808638{col 30}{space 2} .0996063{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4} -.114361{col 71}{space 3} .2760886
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0183518{col 30}{space 2} .2464744{col 41}{space 1}    0.07{col 50}{space 3}0.941{col 58}{space 4}-.4647291{col 71}{space 3} .5014327
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2813814{col 30}{space 2} .1279431{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0306174{col 71}{space 3} .5321453
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2570486{col 30}{space 2}  .086892{col 41}{space 1}   -2.96{col 50}{space 3}0.003{col 58}{space 4}-.4273537{col 71}{space 3}-.0867435
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0802387{col 30}{space 2} .0848363{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.2465148{col 71}{space 3} .0860374
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0008331{col 30}{space 2} .0016604{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.0040873{col 71}{space 3} .0024212
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1372698{col 30}{space 2} .2458864{col 41}{space 1}    0.56{col 50}{space 3}0.577{col 58}{space 4}-.3446588{col 71}{space 3} .6191983
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1418837{col 30}{space 2} .1823119{col 41}{space 1}    0.78{col 50}{space 3}0.436{col 58}{space 4} -.215441{col 71}{space 3} .4992084
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4419593{col 30}{space 2} .1156525{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .2152846{col 71}{space 3} .6686339
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8836997{col 30}{space 2} .2061157{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .4797204{col 71}{space 3} 1.287679
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1550488{col 30}{space 2} .1490965{col 41}{space 1}    1.04{col 50}{space 3}0.298{col 58}{space 4}-.1371749{col 71}{space 3} .4472726
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6672587{col 30}{space 2} .1038328{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .4637501{col 71}{space 3} .8707673
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3684748{col 30}{space 2} .3448305{col 41}{space 1}    1.07{col 50}{space 3}0.285{col 58}{space 4}-.3073807{col 71}{space 3}  1.04433
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2529902{col 30}{space 2}  .052384{col 41}{space 1}   -4.83{col 50}{space 3}0.000{col 58}{space 4}-.3556609{col 71}{space 3}-.1503195
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0164595{col 30}{space 2} .0516566{col 41}{space 1}   -0.32{col 50}{space 3}0.750{col 58}{space 4}-.1177046{col 71}{space 3} .0847856
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.790737{col 30}{space 2} .2019085{col 41}{space 1}   18.77{col 50}{space 3}0.000{col 58}{space 4} 3.395004{col 71}{space 3}  4.18647
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .63771969
         {txt}sigma_e {c |} {res} 1.5886244
             {txt}rho {c |} {res} .13878121{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,811
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,302

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0208                                         {txt}min = {res}         1
{txt}     between = {res}0.3052                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2586                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3483.87
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,302} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0357015{col 30}{space 2} .0201439{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4}-.0037799{col 71}{space 3} .0751829
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0229241{col 30}{space 2} .0055559{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.0338134{col 71}{space 3}-.0120348
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2541022{col 30}{space 2} .0796688{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0979542{col 71}{space 3} .4102503
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0047517{col 30}{space 2} .0013919{col 41}{space 1}    3.41{col 50}{space 3}0.001{col 58}{space 4} .0020236{col 71}{space 3} .0074798
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2483168{col 30}{space 2} .0614717{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .1278345{col 71}{space 3} .3687991
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2371043{col 30}{space 2}  .036851{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .1648778{col 71}{space 3} .3093309
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0644098{col 30}{space 2} .0580122{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4} -.049292{col 71}{space 3} .1781115
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1179374{col 30}{space 2} .0505618{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0188381{col 71}{space 3} .2170366
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0588262{col 30}{space 2} .1020826{col 41}{space 1}   -0.58{col 50}{space 3}0.564{col 58}{space 4}-.2589043{col 71}{space 3}  .141252
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1201732{col 30}{space 2}  .084332{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.0451146{col 71}{space 3}  .285461
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3151216{col 30}{space 2}   .05575{col 41}{space 1}    5.65{col 50}{space 3}0.000{col 58}{space 4} .2058536{col 71}{space 3} .4243895
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0456387{col 30}{space 2}  .067457{col 41}{space 1}    0.68{col 50}{space 3}0.499{col 58}{space 4}-.0865746{col 71}{space 3}  .177852
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0160538{col 30}{space 2} .0108981{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4}-.0374136{col 71}{space 3} .0053061
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2324652{col 30}{space 2} .0664784{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4}   .10217{col 71}{space 3} .3627604
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0478383{col 30}{space 2} .0667127{col 41}{space 1}    0.72{col 50}{space 3}0.473{col 58}{space 4}-.0829162{col 71}{space 3} .1785927
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7270856{col 30}{space 2} .0699892{col 41}{space 1}   10.39{col 50}{space 3}0.000{col 58}{space 4} .5899092{col 71}{space 3}  .864262
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.073764{col 30}{space 2} .0762375{col 41}{space 1}   14.08{col 50}{space 3}0.000{col 58}{space 4} .9243416{col 71}{space 3} 1.223187
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3056731{col 30}{space 2} .0947673{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4} .1199325{col 71}{space 3} .4914137
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1333967{col 30}{space 2} .0672847{col 41}{space 1}    1.98{col 50}{space 3}0.047{col 58}{space 4} .0015211{col 71}{space 3} .2652724
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3895901{col 30}{space 2} .1800079{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0367811{col 71}{space 3} .7423991
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1291762{col 30}{space 2}  .027538{col 41}{space 1}   -4.69{col 50}{space 3}0.000{col 58}{space 4}-.1831496{col 71}{space 3}-.0752028
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2504604{col 30}{space 2} .0618848{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.3717525{col 71}{space 3}-.1291684
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4096896{col 30}{space 2} .0585884{col 41}{space 1}   -6.99{col 50}{space 3}0.000{col 58}{space 4}-.5245207{col 71}{space 3}-.2948585
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.1032574{col 30}{space 2} .0552765{col 41}{space 1}   -1.87{col 50}{space 3}0.062{col 58}{space 4}-.2115973{col 71}{space 3} .0050826
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.404917{col 30}{space 2} .1054353{col 41}{space 1}   32.29{col 50}{space 3}0.000{col 58}{space 4} 3.198267{col 71}{space 3} 3.611566
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .94969253
         {txt}sigma_e {c |} {res} 1.3782269
             {txt}rho {c |} {res} .32194895{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,194
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,280

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0190                                         {txt}min = {res}         1
{txt}     between = {res}0.3660                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.3157                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4485.25
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,280} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0207586{col 30}{space 2} .0166629{col 41}{space 1}    1.25{col 50}{space 3}0.213{col 58}{space 4}   -.0119{col 71}{space 3} .0534173
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0220494{col 30}{space 2} .0069084{col 41}{space 1}   -3.19{col 50}{space 3}0.001{col 58}{space 4}-.0355896{col 71}{space 3}-.0085091
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0325402{col 30}{space 2} .0892385{col 41}{space 1}   -0.36{col 50}{space 3}0.715{col 58}{space 4}-.2074445{col 71}{space 3}  .142364
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005189{col 30}{space 2} .0014747{col 41}{space 1}    0.35{col 50}{space 3}0.725{col 58}{space 4}-.0023715{col 71}{space 3} .0034093
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1068909{col 30}{space 2} .0545295{col 41}{space 1}   -1.96{col 50}{space 3}0.050{col 58}{space 4}-.2137667{col 71}{space 3}-.0000151
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .332948{col 30}{space 2} .0440256{col 41}{space 1}    7.56{col 50}{space 3}0.000{col 58}{space 4} .2466595{col 71}{space 3} .4192366
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1658391{col 30}{space 2} .1038071{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0376192{col 71}{space 3} .3692973
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3242175{col 30}{space 2} .0531296{col 41}{space 1}    6.10{col 50}{space 3}0.000{col 58}{space 4} .2200854{col 71}{space 3} .4283497
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2103907{col 30}{space 2} .1013299{col 41}{space 1}   -2.08{col 50}{space 3}0.038{col 58}{space 4}-.4089936{col 71}{space 3}-.0117877
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0605132{col 30}{space 2} .0517185{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0408531{col 71}{space 3} .1618795
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1981854{col 30}{space 2} .0485942{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} .1029426{col 71}{space 3} .2934282
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1634526{col 30}{space 2} .0580974{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0495837{col 71}{space 3} .2773214
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0060013{col 30}{space 2}   .00413{col 41}{space 1}   -1.45{col 50}{space 3}0.146{col 58}{space 4}-.0140958{col 71}{space 3} .0020933
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1074688{col 30}{space 2} .0366226{col 41}{space 1}   -2.93{col 50}{space 3}0.003{col 58}{space 4}-.1792479{col 71}{space 3}-.0356898
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .6879104{col 30}{space 2} .1317298{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4} .4297247{col 71}{space 3}  .946096
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6787265{col 30}{space 2}   .07314{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .5353746{col 71}{space 3} .8220783
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7646483{col 30}{space 2} .0973049{col 41}{space 1}    7.86{col 50}{space 3}0.000{col 58}{space 4} .5739342{col 71}{space 3} .9553625
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1991948{col 30}{space 2} .0631919{col 41}{space 1}    3.15{col 50}{space 3}0.002{col 58}{space 4} .0753409{col 71}{space 3} .3230486
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6112454{col 30}{space 2} .0664371{col 41}{space 1}    9.20{col 50}{space 3}0.000{col 58}{space 4} .4810311{col 71}{space 3} .7414597
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .9129193{col 30}{space 2}  .180206{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4} .5597219{col 71}{space 3} 1.266117
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2874238{col 30}{space 2} .0216216{col 41}{space 1}  -13.29{col 50}{space 3}0.000{col 58}{space 4}-.3298014{col 71}{space 3}-.2450462
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} -.101546{col 30}{space 2} .0394547{col 41}{space 1}   -2.57{col 50}{space 3}0.010{col 58}{space 4}-.1788758{col 71}{space 3}-.0242163
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0615224{col 30}{space 2} .0330429{col 41}{space 1}   -1.86{col 50}{space 3}0.063{col 58}{space 4}-.1262854{col 71}{space 3} .0032405
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.2093181{col 30}{space 2} .0460601{col 41}{space 1}   -4.54{col 50}{space 3}0.000{col 58}{space 4}-.2995942{col 71}{space 3} -.119042
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.390106{col 30}{space 2} .1189282{col 41}{space 1}   28.51{col 50}{space 3}0.000{col 58}{space 4} 3.157011{col 71}{space 3} 3.623201
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.1507423
         {txt}sigma_e {c |} {res}  1.311273
             {txt}rho {c |} {res} .43507307{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,749
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,278

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0418                                         {txt}min = {res}         1
{txt}     between = {res}0.3184                                         {txt}avg = {res}       3.9
{txt}     overall = {res}0.1936                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2387.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,278} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0193894{col 30}{space 2} .0136569{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0073775{col 71}{space 3} .0461564
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0046463{col 30}{space 2} .0065633{col 41}{space 1}   -0.71{col 50}{space 3}0.479{col 58}{space 4}-.0175101{col 71}{space 3} .0082175
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1855838{col 30}{space 2}  .071321{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.3253703{col 71}{space 3}-.0457972
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0073336{col 30}{space 2} .0013494{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4}-.0099785{col 71}{space 3}-.0046887
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1565073{col 30}{space 2} .0450425{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .0682255{col 71}{space 3}  .244789
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3114646{col 30}{space 2} .0377709{col 41}{space 1}    8.25{col 50}{space 3}0.000{col 58}{space 4} .2374351{col 71}{space 3} .3854942
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1374993{col 30}{space 2}  .067444{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0053116{col 71}{space 3}  .269687
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3071352{col 30}{space 2} .0396193{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .2294827{col 71}{space 3} .3847876
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .6783723{col 30}{space 2} .0582754{col 41}{space 1}   11.64{col 50}{space 3}0.000{col 58}{space 4} .5641546{col 71}{space 3}   .79259
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2776226{col 30}{space 2} .0384525{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .2022571{col 71}{space 3} .3529882
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3057113{col 30}{space 2} .0367808{col 41}{space 1}    8.31{col 50}{space 3}0.000{col 58}{space 4} .2336222{col 71}{space 3} .3778004
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0730806{col 30}{space 2} .0356795{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.1430113{col 71}{space 3}  -.00315
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0012189{col 30}{space 2} .0018196{col 41}{space 1}    0.67{col 50}{space 3}0.503{col 58}{space 4}-.0023474{col 71}{space 3} .0047853
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1268281{col 30}{space 2}  .032293{col 41}{space 1}   -3.93{col 50}{space 3}0.000{col 58}{space 4}-.1901212{col 71}{space 3}-.0635351
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1520038{col 30}{space 2} .1077916{col 41}{space 1}    1.41{col 50}{space 3}0.158{col 58}{space 4}-.0592639{col 71}{space 3} .3632714
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4532748{col 30}{space 2} .0727853{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .3106183{col 71}{space 3} .5959314
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3873698{col 30}{space 2} .0865283{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .2177774{col 71}{space 3} .5569622
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5214477{col 30}{space 2} .0686751{col 41}{space 1}    7.59{col 50}{space 3}0.000{col 58}{space 4}  .386847{col 71}{space 3} .6560484
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7855192{col 30}{space 2} .0661941{col 41}{space 1}   11.87{col 50}{space 3}0.000{col 58}{space 4} .6557812{col 71}{space 3} .9152573
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.7618708{col 30}{space 2} .1486656{col 41}{space 1}   -5.12{col 50}{space 3}0.000{col 58}{space 4} -1.05325{col 71}{space 3}-.4704916
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2050703{col 30}{space 2} .0253984{col 41}{space 1}   -8.07{col 50}{space 3}0.000{col 58}{space 4}-.2548502{col 71}{space 3}-.1552903
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1622544{col 30}{space 2} .0381266{col 41}{space 1}   -4.26{col 50}{space 3}0.000{col 58}{space 4}-.2369812{col 71}{space 3}-.0875276
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} -.116514{col 30}{space 2}  .040188{col 41}{space 1}   -2.90{col 50}{space 3}0.004{col 58}{space 4}-.1952809{col 71}{space 3} -.037747
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2150307{col 30}{space 2} .0383125{col 41}{space 1}    5.61{col 50}{space 3}0.000{col 58}{space 4} .1399396{col 71}{space 3} .2901217
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0620145{col 30}{space 2} .0383018{col 41}{space 1}    1.62{col 50}{space 3}0.105{col 58}{space 4}-.0130556{col 71}{space 3} .1370847
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .1134919{col 30}{space 2} .0369711{col 41}{space 1}    3.07{col 50}{space 3}0.002{col 58}{space 4} .0410298{col 71}{space 3}  .185954
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.265232{col 30}{space 2} .1191391{col 41}{space 1}   27.41{col 50}{space 3}0.000{col 58}{space 4} 3.031724{col 71}{space 3} 3.498741
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0303159
         {txt}sigma_e {c |} {res} 1.4188843
             {txt}rho {c |} {res} .34524411{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S14_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S14_farmer_imr.rtf not found)
(output written to {browse  `"S14_farmer_imr.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                  S15_S18                                     *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(10,046 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0314                                         {txt}min = {res}         1
{txt}     between = {res}0.3611                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2786                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 17626.16
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1189567{col 30}{space 2} .0065495{col 41}{space 1}   18.16{col 50}{space 3}0.000{col 58}{space 4}   .10612{col 71}{space 3} .1317934
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0120183{col 30}{space 2} .0025953{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4}-.0171049{col 71}{space 3}-.0069316
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0734091{col 30}{space 2} .0326198{col 41}{space 1}    2.25{col 50}{space 3}0.024{col 58}{space 4} .0094755{col 71}{space 3} .1373428
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0015209{col 30}{space 2} .0005406{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0004614{col 71}{space 3} .0025803
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0188576{col 30}{space 2} .0211142{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4}-.0225254{col 71}{space 3} .0602406
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2689697{col 30}{space 2} .0163019{col 41}{space 1}   16.50{col 50}{space 3}0.000{col 58}{space 4} .2370185{col 71}{space 3} .3009208
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1452161{col 30}{space 2} .0338423{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .0788863{col 71}{space 3} .2115458
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1420112{col 30}{space 2} .0208009{col 41}{space 1}    6.83{col 50}{space 3}0.000{col 58}{space 4} .1012422{col 71}{space 3} .1827802
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0503787{col 30}{space 2} .0364978{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.0211557{col 71}{space 3} .1219132
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0924228{col 30}{space 2}  .023578{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .0462108{col 71}{space 3} .1386348
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .176874{col 30}{space 2} .0198798{col 41}{space 1}    8.90{col 50}{space 3}0.000{col 58}{space 4} .1379103{col 71}{space 3} .2158377
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0061839{col 30}{space 2} .0201342{col 41}{space 1}   -0.31{col 50}{space 3}0.759{col 58}{space 4}-.0456463{col 71}{space 3} .0332784
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0006447{col 30}{space 2} .0011197{col 41}{space 1}   -0.58{col 50}{space 3}0.565{col 58}{space 4}-.0028393{col 71}{space 3}   .00155
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1121334{col 30}{space 2} .0162523{col 41}{space 1}    6.90{col 50}{space 3}0.000{col 58}{space 4} .0802796{col 71}{space 3} .1439872
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0818664{col 30}{space 2} .0427218{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0018669{col 71}{space 3} .1655996
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5437096{col 30}{space 2} .0292416{col 41}{space 1}   18.59{col 50}{space 3}0.000{col 58}{space 4}  .486397{col 71}{space 3} .6010222
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6476795{col 30}{space 2} .0334963{col 41}{space 1}   19.34{col 50}{space 3}0.000{col 58}{space 4}  .582028{col 71}{space 3}  .713331
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1494253{col 30}{space 2} .0318573{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0869862{col 71}{space 3} .2118645
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .181615{col 30}{space 2} .0270521{col 41}{space 1}    6.71{col 50}{space 3}0.000{col 58}{space 4} .1285939{col 71}{space 3} .2346362
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2688229{col 30}{space 2} .0720459{col 41}{space 1}    3.73{col 50}{space 3}0.000{col 58}{space 4} .1276156{col 71}{space 3} .4100302
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0251059{col 30}{space 2} .0092306{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0070144{col 71}{space 3} .0431975
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.376545{col 30}{space 2}  .035306{col 41}{space 1}  -10.67{col 50}{space 3}0.000{col 58}{space 4}-.4457434{col 71}{space 3}-.3073466
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.536311{col 30}{space 2} .0344169{col 41}{space 1}  -44.64{col 50}{space 3}0.000{col 58}{space 4}-1.603767{col 71}{space 3}-1.468855
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4662423{col 30}{space 2} .0354526{col 41}{space 1}  -13.15{col 50}{space 3}0.000{col 58}{space 4}-.5357281{col 71}{space 3}-.3967565
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2793538{col 30}{space 2} .0346853{col 41}{space 1}   -8.05{col 50}{space 3}0.000{col 58}{space 4}-.3473357{col 71}{space 3} -.211372
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3808981{col 30}{space 2} .0444423{col 41}{space 1}    8.57{col 50}{space 3}0.000{col 58}{space 4} .2937928{col 71}{space 3} .4680033
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2068878{col 30}{space 2} .0473459{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4} -.299684{col 71}{space 3}-.1140915
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0540048{col 30}{space 2} .0357977{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0161573{col 71}{space 3}  .124167
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}  .085861{col 30}{space 2} .0401951{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0070802{col 71}{space 3} .1646419
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0492106{col 30}{space 2} .0365497{col 41}{space 1}    1.35{col 50}{space 3}0.178{col 58}{space 4}-.0224255{col 71}{space 3} .1208468
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1425142{col 30}{space 2} .0404175{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0632974{col 71}{space 3} .2217309
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0764066{col 30}{space 2} .0410832{col 41}{space 1}   -1.86{col 50}{space 3}0.063{col 58}{space 4}-.1569282{col 71}{space 3}  .004115
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2091811{col 30}{space 2} .0394817{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .1317984{col 71}{space 3} .2865638
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1325358{col 30}{space 2} .0614746{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.2530238{col 71}{space 3}-.0120479
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .5567576{col 30}{space 2} .0447261{col 41}{space 1}   12.45{col 50}{space 3}0.000{col 58}{space 4}  .469096{col 71}{space 3} .6444191
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0844039{col 30}{space 2} .0422855{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0015258{col 71}{space 3}  .167282
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.183407{col 30}{space 2} .0649633{col 41}{space 1}   64.40{col 50}{space 3}0.000{col 58}{space 4} 4.056081{col 71}{space 3} 4.310733
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78737539
         {txt}sigma_e {c |} {res} 1.2207094
             {txt}rho {c |} {res} .29380718{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0213                                         {txt}min = {res}         1
{txt}     between = {res}0.3167                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2070                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1928.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0610721{col 30}{space 2} .0116414{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .0382554{col 71}{space 3} .0838888
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0296271{col 30}{space 2} .0075641{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .0148017{col 71}{space 3} .0444524
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0558981{col 30}{space 2} .0670665{col 41}{space 1}    0.83{col 50}{space 3}0.405{col 58}{space 4}-.0755498{col 71}{space 3} .1873459
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0016708{col 30}{space 2} .0011551{col 41}{space 1}   -1.45{col 50}{space 3}0.148{col 58}{space 4}-.0039348{col 71}{space 3} .0005932
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.032841{col 30}{space 2} .0438246{col 41}{space 1}   -0.75{col 50}{space 3}0.454{col 58}{space 4}-.1187357{col 71}{space 3} .0530537
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3018689{col 30}{space 2} .0334791{col 41}{space 1}    9.02{col 50}{space 3}0.000{col 58}{space 4}  .236251{col 71}{space 3} .3674867
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1891505{col 30}{space 2} .1640774{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.5107364{col 71}{space 3} .1324353
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1570038{col 30}{space 2} .0396999{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .0791934{col 71}{space 3} .2348142
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0513488{col 30}{space 2} .0695473{col 41}{space 1}    0.74{col 50}{space 3}0.460{col 58}{space 4}-.0849615{col 71}{space 3}  .187659
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0635836{col 30}{space 2}  .078721{col 41}{space 1}    0.81{col 50}{space 3}0.419{col 58}{space 4}-.0907067{col 71}{space 3}  .217874
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1871236{col 30}{space 2} .0535666{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .0821351{col 71}{space 3} .2921122
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0922024{col 30}{space 2} .0422245{col 41}{space 1}   -2.18{col 50}{space 3}0.029{col 58}{space 4}-.1749609{col 71}{space 3} -.009444
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0084874{col 30}{space 2} .0037035{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0012288{col 71}{space 3} .0157461
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2166553{col 30}{space 2} .0312235{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4} .1554583{col 71}{space 3} .2778522
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}     1.01{col 30}{space 2} .2822995{col 41}{space 1}    3.58{col 50}{space 3}0.000{col 58}{space 4} .4567033{col 71}{space 3} 1.563297
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4232933{col 30}{space 2} .0593302{col 41}{space 1}    7.13{col 50}{space 3}0.000{col 58}{space 4} .3070083{col 71}{space 3} .5395784
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4179319{col 30}{space 2} .0728056{col 41}{space 1}    5.74{col 50}{space 3}0.000{col 58}{space 4} .2752356{col 71}{space 3} .5606282
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3744309{col 30}{space 2} .1156668{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .1477281{col 71}{space 3} .6011337
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1322732{col 30}{space 2} .0669232{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4}  .001106{col 71}{space 3} .2634403
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2893697{col 30}{space 2} .1605874{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0253759{col 71}{space 3} .6041153
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0912783{col 30}{space 2} .0163241{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .0592836{col 71}{space 3}  .123273
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1725745{col 30}{space 2} .0230533{col 41}{space 1}   -7.49{col 50}{space 3}0.000{col 58}{space 4}-.2177582{col 71}{space 3}-.1273909
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.808808{col 30}{space 2}  .098147{col 41}{space 1}   28.62{col 50}{space 3}0.000{col 58}{space 4} 2.616444{col 71}{space 3} 3.001173
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69329802
         {txt}sigma_e {c |} {res}  1.054258
             {txt}rho {c |} {res} .30190029{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0306                                         {txt}min = {res}         1
{txt}     between = {res}0.3898                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2568                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1223.36
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1168113{col 30}{space 2}  .020669{col 41}{space 1}    5.65{col 50}{space 3}0.000{col 58}{space 4} .0763008{col 71}{space 3} .1573217
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0106023{col 30}{space 2} .0119446{col 41}{space 1}   -0.89{col 50}{space 3}0.375{col 58}{space 4}-.0340133{col 71}{space 3} .0128088
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.234526{col 30}{space 2} .1189641{col 41}{space 1}   -1.97{col 50}{space 3}0.049{col 58}{space 4}-.4676913{col 71}{space 3}-.0013607
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0040942{col 30}{space 2} .0019213{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.0078599{col 71}{space 3}-.0003285
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0759662{col 30}{space 2} .0714119{col 41}{space 1}   -1.06{col 50}{space 3}0.287{col 58}{space 4} -.215931{col 71}{space 3} .0639986
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2986719{col 30}{space 2}  .062325{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4} .1765171{col 71}{space 3} .4208267
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2749751{col 30}{space 2} .2173613{col 41}{space 1}    1.27{col 50}{space 3}0.206{col 58}{space 4}-.1510451{col 71}{space 3} .7009954
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1381388{col 30}{space 2} .0759782{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0107758{col 71}{space 3} .2870534
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3571975{col 30}{space 2} .1999818{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0347596{col 71}{space 3} .7491547
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1730113{col 30}{space 2} .0952216{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0136195{col 71}{space 3} .3596421
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2475626{col 30}{space 2}  .062115{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .1258194{col 71}{space 3} .3693058
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2304775{col 30}{space 2} .0683453{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.3644319{col 71}{space 3}-.0965231
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0330566{col 30}{space 2} .0318144{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.0292984{col 71}{space 3} .0954116
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0314482{col 30}{space 2} .0615168{col 41}{space 1}    0.51{col 50}{space 3}0.609{col 58}{space 4}-.0891225{col 71}{space 3} .1520189
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0256658{col 30}{space 2} .3275736{col 41}{space 1}    0.08{col 50}{space 3}0.938{col 58}{space 4}-.6163668{col 71}{space 3} .6676983
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .674163{col 30}{space 2} .1155603{col 41}{space 1}    5.83{col 50}{space 3}0.000{col 58}{space 4}  .447669{col 71}{space 3} .9006571
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.137393{col 30}{space 2} .2252316{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4}  .695947{col 71}{space 3} 1.578839
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4801156{col 30}{space 2} .1290541{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .2271741{col 71}{space 3} .7330571
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3873862{col 30}{space 2} .1087352{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .1742691{col 71}{space 3} .6005032
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.3522327{col 30}{space 2} .2710045{col 41}{space 1}   -1.30{col 50}{space 3}0.194{col 58}{space 4}-.8833918{col 71}{space 3} .1789263
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0540793{col 30}{space 2} .0368589{col 41}{space 1}    1.47{col 50}{space 3}0.142{col 58}{space 4}-.0181629{col 71}{space 3} .1263214
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2700369{col 30}{space 2} .0610344{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1504116{col 71}{space 3} .3896622
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1126769{col 30}{space 2} .0553412{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0042101{col 71}{space 3} .2211437
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.758248{col 30}{space 2} .1847363{col 41}{space 1}   25.76{col 50}{space 3}0.000{col 58}{space 4} 4.396172{col 71}{space 3} 5.120325
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72523365
         {txt}sigma_e {c |} {res}  1.290952
             {txt}rho {c |} {res}    .23989{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0541                                         {txt}min = {res}         1
{txt}     between = {res}0.1715                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1332                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}   864.90
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2841289{col 30}{space 2} .0396687{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .2063796{col 71}{space 3} .3618783
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0089504{col 30}{space 2} .0073121{col 41}{space 1}    1.22{col 50}{space 3}0.221{col 58}{space 4} -.005381{col 71}{space 3} .0232818
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0075688{col 30}{space 2} .1341272{col 41}{space 1}   -0.06{col 50}{space 3}0.955{col 58}{space 4}-.2704533{col 71}{space 3} .2553157
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0047457{col 30}{space 2} .0019312{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0009605{col 71}{space 3} .0085309
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0217901{col 30}{space 2}  .086841{col 41}{space 1}    0.25{col 50}{space 3}0.802{col 58}{space 4} -.148415{col 71}{space 3} .1919952
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2580215{col 30}{space 2} .0580293{col 41}{space 1}    4.45{col 50}{space 3}0.000{col 58}{space 4} .1442862{col 71}{space 3} .3717568
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4503673{col 30}{space 2} .1520778{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .1523002{col 71}{space 3} .7484344
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0188856{col 30}{space 2} .0890572{col 41}{space 1}    0.21{col 50}{space 3}0.832{col 58}{space 4}-.1556633{col 71}{space 3} .1934345
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0415447{col 30}{space 2}  .234991{col 41}{space 1}    0.18{col 50}{space 3}0.860{col 58}{space 4}-.4190293{col 71}{space 3} .5021186
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1987273{col 30}{space 2} .1181978{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0329361{col 71}{space 3} .4303908
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2474876{col 30}{space 2} .0786447{col 41}{space 1}   -3.15{col 50}{space 3}0.002{col 58}{space 4}-.4016283{col 71}{space 3}-.0933468
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0535148{col 30}{space 2} .0776955{col 41}{space 1}   -0.69{col 50}{space 3}0.491{col 58}{space 4}-.2057951{col 71}{space 3} .0987655
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  -.00153{col 30}{space 2} .0015661{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-.0045994{col 71}{space 3} .0015394
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .263696{col 30}{space 2} .2135794{col 41}{space 1}    1.23{col 50}{space 3}0.217{col 58}{space 4}-.1549119{col 71}{space 3} .6823039
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0351491{col 30}{space 2} .1722574{col 41}{space 1}    0.20{col 50}{space 3}0.838{col 58}{space 4}-.3024692{col 71}{space 3} .3727674
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3310293{col 30}{space 2} .1033388{col 41}{space 1}    3.20{col 50}{space 3}0.001{col 58}{space 4}  .128489{col 71}{space 3} .5335696
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6286546{col 30}{space 2} .1943388{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4} .2477575{col 71}{space 3} 1.009552
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0410598{col 30}{space 2} .1339249{col 41}{space 1}    0.31{col 50}{space 3}0.759{col 58}{space 4}-.2214282{col 71}{space 3} .3035478
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4994131{col 30}{space 2} .0934286{col 41}{space 1}    5.35{col 50}{space 3}0.000{col 58}{space 4} .3162965{col 71}{space 3} .6825297
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4067443{col 30}{space 2} .3234384{col 41}{space 1}    1.26{col 50}{space 3}0.209{col 58}{space 4}-.2271833{col 71}{space 3} 1.040672
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1990958{col 30}{space 2} .0473012{col 41}{space 1}   -4.21{col 50}{space 3}0.000{col 58}{space 4}-.2918044{col 71}{space 3}-.1063872
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2657699{col 30}{space 2} .0464903{col 41}{space 1}    5.72{col 50}{space 3}0.000{col 58}{space 4} .1746506{col 71}{space 3} .3568892
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.136172{col 30}{space 2} .1861782{col 41}{space 1}   22.22{col 50}{space 3}0.000{col 58}{space 4} 3.771269{col 71}{space 3} 4.501074
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .52717142
         {txt}sigma_e {c |} {res} 1.4246638
             {txt}rho {c |} {res} .12043358{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0385                                         {txt}min = {res}         1
{txt}     between = {res}0.2957                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2525                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  3418.29
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1187979{col 30}{space 2}  .018036{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4}  .083448{col 71}{space 3} .1541478
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.035838{col 30}{space 2} .0049504{col 41}{space 1}   -7.24{col 50}{space 3}0.000{col 58}{space 4}-.0455406{col 71}{space 3}-.0261353
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2511765{col 30}{space 2} .0698633{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .1142469{col 71}{space 3} .3881061
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0070821{col 30}{space 2} .0012305{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .0046703{col 71}{space 3} .0094938
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2668545{col 30}{space 2} .0530155{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .1629461{col 71}{space 3}  .370763
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1719253{col 30}{space 2} .0330002{col 41}{space 1}    5.21{col 50}{space 3}0.000{col 58}{space 4} .1072461{col 71}{space 3} .2366045
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0343485{col 30}{space 2} .0524469{col 41}{space 1}    0.65{col 50}{space 3}0.513{col 58}{space 4}-.0684456{col 71}{space 3} .1371426
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1198575{col 30}{space 2} .0461636{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0293786{col 71}{space 3} .2103365
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0721308{col 30}{space 2} .0918818{col 41}{space 1}   -0.79{col 50}{space 3}0.432{col 58}{space 4}-.2522158{col 71}{space 3} .1079542
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1865059{col 30}{space 2} .0752118{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0390935{col 71}{space 3} .3339182
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2825166{col 30}{space 2} .0492993{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} .1858918{col 71}{space 3} .3791414
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1245485{col 30}{space 2} .0584006{col 41}{space 1}    2.13{col 50}{space 3}0.033{col 58}{space 4} .0100854{col 71}{space 3} .2390116
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0080967{col 30}{space 2} .0067732{col 41}{space 1}   -1.20{col 50}{space 3}0.232{col 58}{space 4} -.021372{col 71}{space 3} .0051786
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3334181{col 30}{space 2} .0611535{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .2135595{col 71}{space 3} .4532767
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1316159{col 30}{space 2} .0607074{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0126315{col 71}{space 3} .2506002
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7510178{col 30}{space 2}   .06382{col 41}{space 1}   11.77{col 50}{space 3}0.000{col 58}{space 4}  .625933{col 71}{space 3} .8761027
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8557869{col 30}{space 2} .0688289{col 41}{space 1}   12.43{col 50}{space 3}0.000{col 58}{space 4} .7208848{col 71}{space 3}  .990689
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1221885{col 30}{space 2} .0853938{col 41}{space 1}    1.43{col 50}{space 3}0.152{col 58}{space 4}-.0451802{col 71}{space 3} .2895572
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} -.046962{col 30}{space 2} .0595057{col 41}{space 1}   -0.79{col 50}{space 3}0.430{col 58}{space 4}-.1635911{col 71}{space 3} .0696671
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3040589{col 30}{space 2} .1590842{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0077404{col 71}{space 3} .6158582
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0552533{col 30}{space 2}  .024497{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.1032665{col 71}{space 3}-.0072401
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6361269{col 30}{space 2}  .053825{col 41}{space 1}  -11.82{col 50}{space 3}0.000{col 58}{space 4} -.741622{col 71}{space 3}-.5306317
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.6130345{col 30}{space 2} .0524253{col 41}{space 1}  -11.69{col 50}{space 3}0.000{col 58}{space 4}-.7157861{col 71}{space 3}-.5102829
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4431481{col 30}{space 2} .0487929{col 41}{space 1}   -9.08{col 50}{space 3}0.000{col 58}{space 4}-.5387804{col 71}{space 3}-.3475158
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.332612{col 30}{space 2} .0954138{col 41}{space 1}   45.41{col 50}{space 3}0.000{col 58}{space 4} 4.145605{col 71}{space 3}  4.51962
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84906439
         {txt}sigma_e {c |} {res} 1.2179438
             {txt}rho {c |} {res} .32704765{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0464                                         {txt}min = {res}         1
{txt}     between = {res}0.2356                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1881                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1952.30
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2062012{col 30}{space 2} .0147902{col 41}{space 1}   13.94{col 50}{space 3}0.000{col 58}{space 4} .1772128{col 71}{space 3} .2351895
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0120116{col 30}{space 2} .0055267{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.0228438{col 71}{space 3}-.0011794
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2192772{col 30}{space 2} .0758553{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0706035{col 71}{space 3} .3679509
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0024771{col 30}{space 2} .0012459{col 41}{space 1}    1.99{col 50}{space 3}0.047{col 58}{space 4} .0000353{col 71}{space 3}  .004919
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1523787{col 30}{space 2} .0466596{col 41}{space 1}   -3.27{col 50}{space 3}0.001{col 58}{space 4}-.2438298{col 71}{space 3}-.0609277
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1621277{col 30}{space 2} .0381526{col 41}{space 1}    4.25{col 50}{space 3}0.000{col 58}{space 4}   .08735{col 71}{space 3} .2369054
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4340715{col 30}{space 2} .0950967{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .2476854{col 71}{space 3} .6204577
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1680878{col 30}{space 2} .0504193{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0692677{col 71}{space 3} .2669078
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3717035{col 30}{space 2} .0801626{col 41}{space 1}   -4.64{col 50}{space 3}0.000{col 58}{space 4}-.5288192{col 71}{space 3}-.2145877
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0776667{col 30}{space 2} .0481146{col 41}{space 1}   -1.61{col 50}{space 3}0.106{col 58}{space 4}-.1719696{col 71}{space 3} .0166362
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0834659{col 30}{space 2} .0444946{col 41}{space 1}    1.88{col 50}{space 3}0.061{col 58}{space 4}-.0037419{col 71}{space 3} .1706737
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1293699{col 30}{space 2} .0524313{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0266065{col 71}{space 3} .2321333
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0032895{col 30}{space 2} .0032888{col 41}{space 1}   -1.00{col 50}{space 3}0.317{col 58}{space 4}-.0097354{col 71}{space 3} .0031564
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0276416{col 30}{space 2}  .032743{col 41}{space 1}    0.84{col 50}{space 3}0.399{col 58}{space 4}-.0365336{col 71}{space 3} .0918167
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3176301{col 30}{space 2} .1202129{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4}  .082017{col 71}{space 3} .5532431
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4475131{col 30}{space 2}   .06747{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .3152742{col 71}{space 3} .5797519
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4389463{col 30}{space 2} .0796645{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .2828068{col 71}{space 3} .5950859
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0150522{col 30}{space 2} .0572733{col 41}{space 1}   -0.26{col 50}{space 3}0.793{col 58}{space 4}-.1273058{col 71}{space 3} .0972014
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3186959{col 30}{space 2} .0593703{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .2023321{col 71}{space 3} .4350596
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.186678{col 30}{space 2} .1565151{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .8799139{col 71}{space 3} 1.493442
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0744267{col 30}{space 2} .0192017{col 41}{space 1}   -3.88{col 50}{space 3}0.000{col 58}{space 4}-.1120614{col 71}{space 3} -.036792
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.1227682{col 30}{space 2} .0400759{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.2013155{col 71}{space 3} -.044221
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0116736{col 30}{space 2} .0337351{col 41}{space 1}   -0.35{col 50}{space 3}0.729{col 58}{space 4}-.0777931{col 71}{space 3}  .054446
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1512924{col 30}{space 2} .0427033{col 41}{space 1}   -3.54{col 50}{space 3}0.000{col 58}{space 4}-.2349892{col 71}{space 3}-.0675955
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.983794{col 30}{space 2}  .102707{col 41}{space 1}   38.79{col 50}{space 3}0.000{col 58}{space 4} 3.782493{col 71}{space 3} 4.185096
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75192879
         {txt}sigma_e {c |} {res} 1.1917013
             {txt}rho {c |} {res} .28475596{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0532                                         {txt}min = {res}         1
{txt}     between = {res}0.2903                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1957                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2444.44
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1142347{col 30}{space 2} .0127892{col 41}{space 1}    8.93{col 50}{space 3}0.000{col 58}{space 4} .0891683{col 71}{space 3}  .139301
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0013301{col 30}{space 2} .0056418{col 41}{space 1}    0.24{col 50}{space 3}0.814{col 58}{space 4}-.0097276{col 71}{space 3} .0123877
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0928546{col 30}{space 2} .0635886{col 41}{space 1}   -1.46{col 50}{space 3}0.144{col 58}{space 4} -.217486{col 71}{space 3} .0317767
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028956{col 30}{space 2} .0011293{col 41}{space 1}   -2.56{col 50}{space 3}0.010{col 58}{space 4} -.005109{col 71}{space 3}-.0006821
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1589757{col 30}{space 2} .0388463{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .0828384{col 71}{space 3}  .235113
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3786958{col 30}{space 2}  .035546{col 41}{space 1}   10.65{col 50}{space 3}0.000{col 58}{space 4} .3090271{col 71}{space 3} .4483646
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1049441{col 30}{space 2} .0610469{col 41}{space 1}    1.72{col 50}{space 3}0.086{col 58}{space 4}-.0147057{col 71}{space 3} .2245938
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2633153{col 30}{space 2} .0383975{col 41}{space 1}    6.86{col 50}{space 3}0.000{col 58}{space 4} .1880576{col 71}{space 3} .3385729
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5600468{col 30}{space 2} .0526291{col 41}{space 1}   10.64{col 50}{space 3}0.000{col 58}{space 4} .4568958{col 71}{space 3} .6631979
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1384766{col 30}{space 2} .0351729{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4}  .069539{col 71}{space 3} .2074141
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .245262{col 30}{space 2}  .034032{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .1785606{col 71}{space 3} .3119634
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1326533{col 30}{space 2} .0327735{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.1968882{col 71}{space 3}-.0684184
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0014815{col 30}{space 2}  .001605{col 41}{space 1}    0.92{col 50}{space 3}0.356{col 58}{space 4}-.0016641{col 71}{space 3} .0046272
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0155348{col 30}{space 2} .0276652{col 41}{space 1}    0.56{col 50}{space 3}0.574{col 58}{space 4} -.038688{col 71}{space 3} .0697576
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1850615{col 30}{space 2}  .088893{col 41}{space 1}    2.08{col 50}{space 3}0.037{col 58}{space 4} .0108344{col 71}{space 3} .3592887
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3490303{col 30}{space 2} .0636546{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4} .2242697{col 71}{space 3}  .473791
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3215892{col 30}{space 2} .0729183{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4}  .178672{col 71}{space 3} .4645064
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2096905{col 30}{space 2}  .057528{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .0969376{col 71}{space 3} .3224434
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3191672{col 30}{space 2} .0555357{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .2103194{col 71}{space 3} .4280151
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.7731082{col 30}{space 2} .1336227{col 41}{space 1}   -5.79{col 50}{space 3}0.000{col 58}{space 4}-1.035004{col 71}{space 3}-.5112126
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1280741{col 30}{space 2} .0224318{col 41}{space 1}    5.71{col 50}{space 3}0.000{col 58}{space 4} .0841085{col 71}{space 3} .1720397
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1450009{col 30}{space 2} .0401445{col 41}{space 1}   -3.61{col 50}{space 3}0.000{col 58}{space 4}-.2236826{col 71}{space 3}-.0663192
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0253604{col 30}{space 2} .0369273{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.0977366{col 71}{space 3} .0470159
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3574804{col 30}{space 2} .0350675{col 41}{space 1}   10.19{col 50}{space 3}0.000{col 58}{space 4} .2887493{col 71}{space 3} .4262115
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1081102{col 30}{space 2} .0354521{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0386254{col 71}{space 3}  .177595
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2472669{col 30}{space 2} .0344176{col 41}{space 1}    7.18{col 50}{space 3}0.000{col 58}{space 4} .1798096{col 71}{space 3} .3147242
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.710865{col 30}{space 2}  .104279{col 41}{space 1}   35.59{col 50}{space 3}0.000{col 58}{space 4} 3.506482{col 71}{space 3} 3.915248
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75890295
         {txt}sigma_e {c |} {res} 1.2424406
             {txt}rho {c |} {res} .27171909{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. 
. esttab using  S15_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons )
{res}{txt}(note: file S15_farmer_imr.rtf not found)
(output written to {browse  `"S15_farmer_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. *                          vill_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0220                                         {txt}min = {res}         1
{txt}     between = {res}0.3687                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2787                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 17540.58
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0488215{col 30}{space 2} .0077967{col 41}{space 1}    6.26{col 50}{space 3}0.000{col 58}{space 4} .0335403{col 71}{space 3} .0641028
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0528488{col 30}{space 2} .0028448{col 41}{space 1}  -18.58{col 50}{space 3}0.000{col 58}{space 4}-.0584245{col 71}{space 3}-.0472731
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0005309{col 30}{space 2}  .002554{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-.0055366{col 71}{space 3} .0044748
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0493851{col 30}{space 2} .0327403{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0147847{col 71}{space 3} .1135549
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0009744{col 30}{space 2} .0005422{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0000884{col 71}{space 3} .0020371
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0053421{col 30}{space 2} .0212279{col 41}{space 1}   -0.25{col 50}{space 3}0.801{col 58}{space 4} -.046948{col 71}{space 3} .0362638
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2753764{col 30}{space 2} .0163072{col 41}{space 1}   16.89{col 50}{space 3}0.000{col 58}{space 4}  .243415{col 71}{space 3} .3073379
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1330392{col 30}{space 2} .0339126{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .0665717{col 71}{space 3} .1995068
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1535775{col 30}{space 2} .0208954{col 41}{space 1}    7.35{col 50}{space 3}0.000{col 58}{space 4} .1126233{col 71}{space 3} .1945316
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0839468{col 30}{space 2}  .036595{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0122219{col 71}{space 3} .1556716
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1070813{col 30}{space 2} .0237074{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .0606157{col 71}{space 3}  .153547
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1906926{col 30}{space 2} .0199623{col 41}{space 1}    9.55{col 50}{space 3}0.000{col 58}{space 4} .1515671{col 71}{space 3} .2298181
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0003602{col 30}{space 2} .0202175{col 41}{space 1}   -0.02{col 50}{space 3}0.986{col 58}{space 4}-.0399858{col 71}{space 3} .0392654
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006209{col 30}{space 2}  .001099{col 41}{space 1}    0.56{col 50}{space 3}0.572{col 58}{space 4}-.0015331{col 71}{space 3} .0027749
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1474949{col 30}{space 2} .0162012{col 41}{space 1}    9.10{col 50}{space 3}0.000{col 58}{space 4} .1157411{col 71}{space 3} .1792486
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0827504{col 30}{space 2} .0424761{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0005012{col 71}{space 3}  .166002
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5121858{col 30}{space 2}  .029287{col 41}{space 1}   17.49{col 50}{space 3}0.000{col 58}{space 4} .4547842{col 71}{space 3} .5695873
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .561751{col 30}{space 2} .0333832{col 41}{space 1}   16.83{col 50}{space 3}0.000{col 58}{space 4} .4963211{col 71}{space 3} .6271809
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0791543{col 30}{space 2}  .031936{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0165609{col 71}{space 3} .1417477
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1428102{col 30}{space 2} .0270328{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .0898269{col 71}{space 3} .1957935
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .1892038{col 30}{space 2} .0723181{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4}  .047463{col 71}{space 3} .3309446
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1023274{col 30}{space 2} .0100257{col 41}{space 1}   10.21{col 50}{space 3}0.000{col 58}{space 4} .0826773{col 71}{space 3} .1219775
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.6134682{col 30}{space 2} .0373139{col 41}{space 1}  -16.44{col 50}{space 3}0.000{col 58}{space 4}-.6866021{col 71}{space 3}-.5403344
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.829254{col 30}{space 2} .0378963{col 41}{space 1}  -48.27{col 50}{space 3}0.000{col 58}{space 4}-1.903529{col 71}{space 3}-1.754979
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.7807911{col 30}{space 2} .0394911{col 41}{space 1}  -19.77{col 50}{space 3}0.000{col 58}{space 4}-.8581922{col 71}{space 3}  -.70339
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} -.728905{col 30}{space 2} .0426084{col 41}{space 1}  -17.11{col 50}{space 3}0.000{col 58}{space 4}-.8124158{col 71}{space 3}-.6453941
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1675839{col 30}{space 2} .0458802{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} .0776605{col 71}{space 3} .2575074
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2302236{col 30}{space 2} .0477125{col 41}{space 1}   -4.83{col 50}{space 3}0.000{col 58}{space 4}-.3237383{col 71}{space 3}-.1367088
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0855173{col 30}{space 2} .0362599{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0144491{col 71}{space 3} .1565854
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0927187{col 30}{space 2} .0406751{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0129969{col 71}{space 3} .1724404
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}  .064186{col 30}{space 2} .0369128{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0081617{col 71}{space 3} .1365337
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1618316{col 30}{space 2} .0409733{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .0815255{col 71}{space 3} .2421378
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0566103{col 30}{space 2} .0418175{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.1385712{col 71}{space 3} .0253505
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .229701{col 30}{space 2} .0399001{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .1514982{col 71}{space 3} .3079038
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2072659{col 30}{space 2} .0614841{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.3277726{col 71}{space 3}-.0867593
{txt}{space 11}2018  {c |}{col 18}{res}{space 2}  .521933{col 30}{space 2} .0448808{col 41}{space 1}   11.63{col 50}{space 3}0.000{col 58}{space 4} .4339682{col 71}{space 3} .6098978
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0576282{col 30}{space 2} .0426042{col 41}{space 1}    1.35{col 50}{space 3}0.176{col 58}{space 4}-.0258746{col 71}{space 3} .1411309
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.608504{col 30}{space 2} .0764218{col 41}{space 1}   60.30{col 50}{space 3}0.000{col 58}{space 4}  4.45872{col 71}{space 3} 4.758288
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}   .773342
         {txt}sigma_e {c |} {res} 1.2263994
             {txt}rho {c |} {res} .28450313{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0175                                         {txt}min = {res}         1
{txt}     between = {res}0.3203                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2060                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1972.01
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0513107{col 30}{space 2} .0162028{col 41}{space 1}    3.17{col 50}{space 3}0.002{col 58}{space 4} .0195539{col 71}{space 3} .0830676
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0464094{col 30}{space 2} .0096995{col 41}{space 1}   -4.78{col 50}{space 3}0.000{col 58}{space 4}  -.06542{col 71}{space 3}-.0273988
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0516193{col 30}{space 2}  .007443{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4} .0370313{col 71}{space 3} .0662072
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0105501{col 30}{space 2} .0672608{col 41}{space 1}   -0.16{col 50}{space 3}0.875{col 58}{space 4}-.1423789{col 71}{space 3} .1212787
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020153{col 30}{space 2} .0011549{col 41}{space 1}   -1.74{col 50}{space 3}0.081{col 58}{space 4}-.0042789{col 71}{space 3} .0002483
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0522284{col 30}{space 2} .0438971{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.1382651{col 71}{space 3} .0338082
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3194385{col 30}{space 2} .0334756{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .2538275{col 71}{space 3} .3850495
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2023076{col 30}{space 2} .1631533{col 41}{space 1}   -1.24{col 50}{space 3}0.215{col 58}{space 4}-.5220823{col 71}{space 3}  .117467
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1701601{col 30}{space 2} .0397419{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0922673{col 71}{space 3} .2480528
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1265217{col 30}{space 2} .0695426{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0097793{col 71}{space 3} .2628227
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0887613{col 30}{space 2} .0783519{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4}-.0648056{col 71}{space 3} .2423282
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1983498{col 30}{space 2} .0536051{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0932856{col 71}{space 3} .3034139
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1069666{col 30}{space 2} .0421993{col 41}{space 1}   -2.53{col 50}{space 3}0.011{col 58}{space 4}-.1896757{col 71}{space 3}-.0242576
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0145781{col 30}{space 2} .0037995{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0071311{col 71}{space 3}  .022025
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2384852{col 30}{space 2} .0316505{col 41}{space 1}    7.53{col 50}{space 3}0.000{col 58}{space 4} .1764514{col 71}{space 3}  .300519
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9107472{col 30}{space 2} .2772795{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .3672893{col 71}{space 3} 1.454205
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4453633{col 30}{space 2} .0592203{col 41}{space 1}    7.52{col 50}{space 3}0.000{col 58}{space 4} .3292937{col 71}{space 3} .5614329
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3096352{col 30}{space 2} .0732311{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .1661049{col 71}{space 3} .4531656
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3163258{col 30}{space 2}  .114829{col 41}{space 1}    2.75{col 50}{space 3}0.006{col 58}{space 4} .0912651{col 71}{space 3} .5413864
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0890318{col 30}{space 2} .0669508{col 41}{space 1}    1.33{col 50}{space 3}0.184{col 58}{space 4}-.0421893{col 71}{space 3} .2202529
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .0932468{col 30}{space 2} .1608605{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.2220339{col 71}{space 3} .4085275
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1055556{col 30}{space 2} .0198492{col 41}{space 1}    5.32{col 50}{space 3}0.000{col 58}{space 4} .0666519{col 71}{space 3} .1444594
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1584001{col 30}{space 2} .0231221{col 41}{space 1}   -6.85{col 50}{space 3}0.000{col 58}{space 4}-.2037186{col 71}{space 3}-.1130816
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.844955{col 30}{space 2} .1428667{col 41}{space 1}   19.91{col 50}{space 3}0.000{col 58}{space 4} 2.564942{col 71}{space 3} 3.124969
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69021138
         {txt}sigma_e {c |} {res} 1.0559926
             {txt}rho {c |} {res} .29933279{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0189                                         {txt}min = {res}         1
{txt}     between = {res}0.3973                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2524                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1259.08
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0502312{col 30}{space 2} .0279322{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0045148{col 71}{space 3} .1049773
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0573074{col 30}{space 2} .0124377{col 41}{space 1}   -4.61{col 50}{space 3}0.000{col 58}{space 4}-.0816847{col 71}{space 3}  -.03293
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0044615{col 30}{space 2}  .011972{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.0279263{col 71}{space 3} .0190032
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2282263{col 30}{space 2} .1186459{col 41}{space 1}   -1.92{col 50}{space 3}0.054{col 58}{space 4} -.460768{col 71}{space 3} .0043154
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0037763{col 30}{space 2}  .001905{col 41}{space 1}   -1.98{col 50}{space 3}0.047{col 58}{space 4}-.0075101{col 71}{space 3}-.0000425
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0568226{col 30}{space 2} .0717042{col 41}{space 1}   -0.79{col 50}{space 3}0.428{col 58}{space 4}-.1973603{col 71}{space 3} .0837151
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3355293{col 30}{space 2} .0628536{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .2123384{col 71}{space 3} .4587202
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2342755{col 30}{space 2} .2175377{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.1920905{col 71}{space 3} .6606416
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .157161{col 30}{space 2} .0761802{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0078506{col 71}{space 3} .3064714
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4117111{col 30}{space 2} .1975396{col 41}{space 1}    2.08{col 50}{space 3}0.037{col 58}{space 4} .0245406{col 71}{space 3} .7988815
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1803492{col 30}{space 2} .0965853{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0089546{col 71}{space 3} .3696529
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2662326{col 30}{space 2} .0620609{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .1445956{col 71}{space 3} .3878697
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2334027{col 30}{space 2} .0683597{col 41}{space 1}   -3.41{col 50}{space 3}0.001{col 58}{space 4}-.3673852{col 71}{space 3}-.0994201
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1016061{col 30}{space 2} .0356825{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0316697{col 71}{space 3} .1715426
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0959608{col 30}{space 2} .0627735{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4} -.027073{col 71}{space 3} .2189946
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2161924{col 30}{space 2} .3353716{col 41}{space 1}    0.64{col 50}{space 3}0.519{col 58}{space 4}-.4411239{col 71}{space 3} .8735087
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6487176{col 30}{space 2} .1161269{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .4211131{col 71}{space 3} .8763221
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7795382{col 30}{space 2} .2267756{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} .3350661{col 71}{space 3}  1.22401
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3239096{col 30}{space 2} .1312034{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0667556{col 71}{space 3} .5810636
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3029234{col 30}{space 2} .1079813{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4}  .091284{col 71}{space 3} .5145628
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.4831193{col 30}{space 2} .2674518{col 41}{space 1}   -1.81{col 50}{space 3}0.071{col 58}{space 4}-1.007315{col 71}{space 3} .0410766
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0276775{col 30}{space 2} .0450908{col 41}{space 1}   -0.61{col 50}{space 3}0.539{col 58}{space 4}-.1160538{col 71}{space 3} .0606988
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .4320119{col 30}{space 2} .0719849{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .2909242{col 71}{space 3} .5730997
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1603678{col 30}{space 2} .0558763{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0508524{col 71}{space 3} .2698833
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.764439{col 30}{space 2} .2709292{col 41}{space 1}   21.28{col 50}{space 3}0.000{col 58}{space 4} 5.233427{col 71}{space 3}  6.29545
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7087949
         {txt}sigma_e {c |} {res} 1.2962721
             {txt}rho {c |} {res} .23016793{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0362                                         {txt}min = {res}         1
{txt}     between = {res}0.1943                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1411                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}   939.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1650497{col 30}{space 2} .0358981{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .0946908{col 71}{space 3} .2354086
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.065912{col 30}{space 2} .0075003{col 41}{space 1}   -8.79{col 50}{space 3}0.000{col 58}{space 4}-.0806123{col 71}{space 3}-.0512118
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138801{col 30}{space 2} .0070173{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0001264{col 71}{space 3} .0276337
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0311526{col 30}{space 2}  .133801{col 41}{space 1}    0.23{col 50}{space 3}0.816{col 58}{space 4}-.2310927{col 71}{space 3} .2933978
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0026721{col 30}{space 2} .0019493{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0011486{col 71}{space 3} .0064927
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0197146{col 30}{space 2} .0861634{col 41}{space 1}   -0.23{col 50}{space 3}0.819{col 58}{space 4}-.1885918{col 71}{space 3} .1491626
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2636586{col 30}{space 2}  .058011{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1499591{col 71}{space 3}  .377358
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4764682{col 30}{space 2} .1540649{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .1745064{col 71}{space 3} .7784299
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0544024{col 30}{space 2} .0902603{col 41}{space 1}    0.60{col 50}{space 3}0.547{col 58}{space 4}-.1225047{col 71}{space 3} .2313094
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0093685{col 30}{space 2}  .240427{col 41}{space 1}   -0.04{col 50}{space 3}0.969{col 58}{space 4}-.4805968{col 71}{space 3} .4618598
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2358382{col 30}{space 2} .1191648{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0022796{col 71}{space 3} .4693969
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2210624{col 30}{space 2} .0802845{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.3784172{col 71}{space 3}-.0637076
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0264528{col 30}{space 2} .0775452{col 41}{space 1}   -0.34{col 50}{space 3}0.733{col 58}{space 4}-.1784386{col 71}{space 3}  .125533
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.000993{col 30}{space 2} .0015052{col 41}{space 1}   -0.66{col 50}{space 3}0.509{col 58}{space 4} -.003943{col 71}{space 3} .0019571
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2738096{col 30}{space 2} .2189152{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.1552563{col 71}{space 3} .7028754
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0558658{col 30}{space 2} .1734545{col 41}{space 1}   -0.32{col 50}{space 3}0.747{col 58}{space 4}-.3958303{col 71}{space 3} .2840988
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1617668{col 30}{space 2} .1048987{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0438309{col 71}{space 3} .3673644
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4020498{col 30}{space 2} .2016649{col 41}{space 1}    1.99{col 50}{space 3}0.046{col 58}{space 4} .0067938{col 71}{space 3} .7973058
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1296654{col 30}{space 2} .1351411{col 41}{space 1}   -0.96{col 50}{space 3}0.337{col 58}{space 4}-.3945371{col 71}{space 3} .1352063
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4271729{col 30}{space 2} .0952227{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .2405399{col 71}{space 3}  .613806
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2723758{col 30}{space 2} .3236985{col 41}{space 1}    0.84{col 50}{space 3}0.400{col 58}{space 4}-.3620617{col 71}{space 3} .9068133
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0744332{col 30}{space 2} .0409557{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4}-.1547048{col 71}{space 3} .0058385
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2957627{col 30}{space 2} .0474971{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .2026701{col 71}{space 3} .3888554
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.098585{col 30}{space 2} .2210469{col 41}{space 1}   23.07{col 50}{space 3}0.000{col 58}{space 4} 4.665341{col 71}{space 3} 5.531829
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .4633219
         {txt}sigma_e {c |} {res} 1.4350675
             {txt}rho {c |} {res} .09439713{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0351                                         {txt}min = {res}         1
{txt}     between = {res}0.3243                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2744                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  3973.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0595827{col 30}{space 2} .0179069{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0244859{col 71}{space 3} .0946795
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.109681{col 30}{space 2} .0085153{col 41}{space 1}  -12.88{col 50}{space 3}0.000{col 58}{space 4}-.1263707{col 71}{space 3}-.0929912
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0219123{col 30}{space 2} .0049366{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4}-.0315878{col 71}{space 3}-.0122368
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2183228{col 30}{space 2} .0691471{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .0827968{col 71}{space 3} .3538487
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .004433{col 30}{space 2} .0012123{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4}  .002057{col 71}{space 3} .0068091
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2298419{col 30}{space 2} .0522683{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .1273978{col 71}{space 3}  .332286
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1651737{col 30}{space 2} .0325892{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4}    .1013{col 71}{space 3} .2290473
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0172254{col 30}{space 2} .0523403{col 41}{space 1}    0.33{col 50}{space 3}0.742{col 58}{space 4}-.0853598{col 71}{space 3} .1198106
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1258225{col 30}{space 2}   .04616{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4} .0353506{col 71}{space 3} .2162945
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0335564{col 30}{space 2} .0913582{col 41}{space 1}   -0.37{col 50}{space 3}0.713{col 58}{space 4}-.2126153{col 71}{space 3} .1455024
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1927372{col 30}{space 2} .0745178{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4}  .046685{col 71}{space 3} .3387894
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2835852{col 30}{space 2}  .049237{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .1870824{col 71}{space 3}  .380088
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1314595{col 30}{space 2} .0578777{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0180214{col 71}{space 3} .2448976
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0043867{col 30}{space 2} .0053634{col 41}{space 1}   -0.82{col 50}{space 3}0.413{col 58}{space 4}-.0148988{col 71}{space 3} .0061255
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2995354{col 30}{space 2} .0607637{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .1804406{col 71}{space 3} .4186301
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1407329{col 30}{space 2} .0599798{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0231746{col 71}{space 3} .2582913
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6489228{col 30}{space 2} .0635909{col 41}{space 1}   10.20{col 50}{space 3}0.000{col 58}{space 4} .5242869{col 71}{space 3} .7735588
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7081497{col 30}{space 2} .0689604{col 41}{space 1}   10.27{col 50}{space 3}0.000{col 58}{space 4} .5729898{col 71}{space 3} .8433096
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0912663{col 30}{space 2} .0847424{col 41}{space 1}    1.08{col 50}{space 3}0.281{col 58}{space 4}-.0748258{col 71}{space 3} .2573584
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0575144{col 30}{space 2} .0588944{col 41}{space 1}   -0.98{col 50}{space 3}0.329{col 58}{space 4}-.1729453{col 71}{space 3} .0579166
{txt}{space 13}imr {c |}{col 18}{res}{space 2}  .214508{col 30}{space 2}  .157851{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.0948742{col 71}{space 3} .5238903
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1609838{col 30}{space 2} .0221775{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .1175166{col 71}{space 3}  .204451
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5518537{col 30}{space 2} .0533825{col 41}{space 1}  -10.34{col 50}{space 3}0.000{col 58}{space 4}-.6564815{col 71}{space 3} -.447226
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5550127{col 30}{space 2} .0516245{col 41}{space 1}  -10.75{col 50}{space 3}0.000{col 58}{space 4}-.6561948{col 71}{space 3}-.4538306
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4136773{col 30}{space 2} .0481273{col 41}{space 1}   -8.60{col 50}{space 3}0.000{col 58}{space 4}-.5080051{col 71}{space 3}-.3193495
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.621734{col 30}{space 2} .1253715{col 41}{space 1}   36.86{col 50}{space 3}0.000{col 58}{space 4} 4.376011{col 71}{space 3} 4.867458
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80465432
         {txt}sigma_e {c |} {res} 1.2204408
             {txt}rho {c |} {res} .30298803{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0161                                         {txt}min = {res}         1
{txt}     between = {res}0.2270                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1690                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1657.67
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0672346{col 30}{space 2} .0203931{col 41}{space 1}    3.30{col 50}{space 3}0.001{col 58}{space 4}  .027265{col 71}{space 3} .1072043
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0405295{col 30}{space 2} .0075098{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.0552484{col 71}{space 3}-.0258107
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0028282{col 30}{space 2} .0054455{col 41}{space 1}   -0.52{col 50}{space 3}0.604{col 58}{space 4}-.0135012{col 71}{space 3} .0078449
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1926916{col 30}{space 2} .0767683{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0422284{col 71}{space 3} .3431547
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0031229{col 30}{space 2} .0012663{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0006409{col 71}{space 3} .0056048
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1612817{col 30}{space 2} .0474123{col 41}{space 1}   -3.40{col 50}{space 3}0.001{col 58}{space 4}-.2542081{col 71}{space 3}-.0683553
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1739739{col 30}{space 2} .0384738{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .0985667{col 71}{space 3} .2493811
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4314203{col 30}{space 2} .0969791{col 41}{space 1}    4.45{col 50}{space 3}0.000{col 58}{space 4} .2413447{col 71}{space 3} .6214959
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2053177{col 30}{space 2} .0513288{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .1047152{col 71}{space 3} .3059203
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3356519{col 30}{space 2} .0826652{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.4976726{col 71}{space 3}-.1736311
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0392934{col 30}{space 2} .0486795{col 41}{space 1}   -0.81{col 50}{space 3}0.420{col 58}{space 4}-.1347035{col 71}{space 3} .0561166
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1139667{col 30}{space 2}   .04487{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4}  .026023{col 71}{space 3} .2019103
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1194958{col 30}{space 2} .0535141{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .0146102{col 71}{space 3} .2243815
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .002704{col 30}{space 2} .0030773{col 41}{space 1}    0.88{col 50}{space 3}0.380{col 58}{space 4}-.0033273{col 71}{space 3} .0087353
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1306484{col 30}{space 2}  .032648{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .0666594{col 71}{space 3} .1946373
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3020463{col 30}{space 2} .1215945{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .0637255{col 71}{space 3} .5403672
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4290937{col 30}{space 2}  .068471{col 41}{space 1}    6.27{col 50}{space 3}0.000{col 58}{space 4} .2948931{col 71}{space 3} .5632943
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4120195{col 30}{space 2} .0804506{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .2543393{col 71}{space 3} .5696998
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0576756{col 30}{space 2} .0578146{col 41}{space 1}   -1.00{col 50}{space 3}0.318{col 58}{space 4}-.1709901{col 71}{space 3} .0556389
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2698231{col 30}{space 2} .0598916{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .1524377{col 71}{space 3} .3872086
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.080858{col 30}{space 2} .1609006{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .7654989{col 71}{space 3} 1.396218
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} -.022203{col 30}{space 2} .0249729{col 41}{space 1}   -0.89{col 50}{space 3}0.374{col 58}{space 4}-.0711489{col 71}{space 3} .0267428
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0899653{col 30}{space 2}  .040289{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}-.1689303{col 71}{space 3}-.0110004
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0218835{col 30}{space 2} .0340337{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.0885884{col 71}{space 3} .0448213
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0827361{col 30}{space 2} .0454393{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4}-.1717954{col 71}{space 3} .0063233
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.315739{col 30}{space 2} .1310782{col 41}{space 1}   32.92{col 50}{space 3}0.000{col 58}{space 4}  4.05883{col 71}{space 3} 4.572647
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7462669
         {txt}sigma_e {c |} {res} 1.2113901
             {txt}rho {c |} {res} .27510359{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0461                                         {txt}min = {res}         1
{txt}     between = {res}0.2930                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1899                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}  2315.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0285518{col 30}{space 2} .0139931{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0011259{col 71}{space 3} .0559778
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0343821{col 30}{space 2} .0048402{col 41}{space 1}   -7.10{col 50}{space 3}0.000{col 58}{space 4}-.0438688{col 71}{space 3}-.0248954
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0178042{col 30}{space 2} .0056069{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .0068148{col 71}{space 3} .0287936
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1349776{col 30}{space 2} .0648159{col 41}{space 1}   -2.08{col 50}{space 3}0.037{col 58}{space 4}-.2620143{col 71}{space 3}-.0079408
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0027069{col 30}{space 2} .0011347{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-.0049308{col 71}{space 3} -.000483
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1484548{col 30}{space 2} .0393997{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .0712329{col 71}{space 3} .2256768
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3924958{col 30}{space 2} .0357378{col 41}{space 1}   10.98{col 50}{space 3}0.000{col 58}{space 4} .3224511{col 71}{space 3} .4625405
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0988083{col 30}{space 2} .0608201{col 41}{space 1}    1.62{col 50}{space 3}0.104{col 58}{space 4} -.020397{col 71}{space 3} .2180135
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2703568{col 30}{space 2} .0386192{col 41}{space 1}    7.00{col 50}{space 3}0.000{col 58}{space 4} .1946646{col 71}{space 3} .3460491
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5819196{col 30}{space 2} .0528395{col 41}{space 1}   11.01{col 50}{space 3}0.000{col 58}{space 4} .4783561{col 71}{space 3} .6854832
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1433767{col 30}{space 2} .0352392{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .0743091{col 71}{space 3} .2124443
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2590098{col 30}{space 2} .0340986{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} .1921778{col 71}{space 3} .3258418
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1236001{col 30}{space 2} .0328715{col 41}{space 1}   -3.76{col 50}{space 3}0.000{col 58}{space 4} -.188027{col 71}{space 3}-.0591731
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0024068{col 30}{space 2} .0017828{col 41}{space 1}    1.35{col 50}{space 3}0.177{col 58}{space 4}-.0010874{col 71}{space 3} .0059011
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0297251{col 30}{space 2} .0279056{col 41}{space 1}    1.07{col 50}{space 3}0.287{col 58}{space 4}-.0249688{col 71}{space 3}  .084419
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1704916{col 30}{space 2} .0886853{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0033284{col 71}{space 3} .3443116
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3598128{col 30}{space 2}  .063777{col 41}{space 1}    5.64{col 50}{space 3}0.000{col 58}{space 4} .2348122{col 71}{space 3} .4848134
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3047971{col 30}{space 2} .0728187{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4}  .162075{col 71}{space 3} .4475191
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1388365{col 30}{space 2} .0574588{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0262192{col 71}{space 3} .2514537
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2813576{col 30}{space 2} .0554711{col 41}{space 1}    5.07{col 50}{space 3}0.000{col 58}{space 4} .1726363{col 71}{space 3} .3900789
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.8288522{col 30}{space 2} .1333334{col 41}{space 1}   -6.22{col 50}{space 3}0.000{col 58}{space 4}-1.090181{col 71}{space 3}-.5675235
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .2102867{col 30}{space 2} .0236208{col 41}{space 1}    8.90{col 50}{space 3}0.000{col 58}{space 4} .1639907{col 71}{space 3} .2565827
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1116817{col 30}{space 2} .0403769{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4} -.190819{col 71}{space 3}-.0325444
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0247769{col 30}{space 2} .0376536{col 41}{space 1}    0.66{col 50}{space 3}0.511{col 58}{space 4}-.0490227{col 71}{space 3} .0985765
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3808055{col 30}{space 2} .0356754{col 41}{space 1}   10.67{col 50}{space 3}0.000{col 58}{space 4}  .310883{col 71}{space 3} .4507279
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1354987{col 30}{space 2} .0357117{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .0655049{col 71}{space 3} .2054924
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2325078{col 30}{space 2} .0344925{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .1649037{col 71}{space 3} .3001119
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.373863{col 30}{space 2} .1431238{col 41}{space 1}   23.57{col 50}{space 3}0.000{col 58}{space 4} 3.093345{col 71}{space 3}  3.65438
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75525049
         {txt}sigma_e {c |} {res} 1.2471583
             {txt}rho {c |} {res} .26832318{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S16_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill _cons)
{res}{txt}(note: file S16_farmer_imr.rtf not found)
(output written to {browse  `"S16_farmer_imr.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. *                          town_village_level                                  *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0232                                         {txt}min = {res}         1
{txt}     between = {res}0.3603                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2738                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 17031.54
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0265085{col 30}{space 2} .0081528{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .0105293{col 71}{space 3} .0424877
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0020964{col 30}{space 2} .0002318{col 41}{space 1}   -9.04{col 50}{space 3}0.000{col 58}{space 4}-.0025508{col 71}{space 3} -.001642
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0008247{col 30}{space 2} .0025691{col 41}{space 1}   -0.32{col 50}{space 3}0.748{col 58}{space 4}  -.00586{col 71}{space 3} .0042106
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0490757{col 30}{space 2} .0328118{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0152342{col 71}{space 3} .1133857
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0018374{col 30}{space 2} .0005425{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .0007741{col 71}{space 3} .0029007
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0060766{col 30}{space 2} .0212907{col 41}{space 1}   -0.29{col 50}{space 3}0.775{col 58}{space 4}-.0478057{col 71}{space 3} .0356525
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2778869{col 30}{space 2} .0163653{col 41}{space 1}   16.98{col 50}{space 3}0.000{col 58}{space 4} .2458115{col 71}{space 3} .3099622
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1457755{col 30}{space 2} .0339409{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .0792525{col 71}{space 3} .2122984
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1529097{col 30}{space 2} .0208789{col 41}{space 1}    7.32{col 50}{space 3}0.000{col 58}{space 4} .1119878{col 71}{space 3} .1938315
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0659156{col 30}{space 2} .0365883{col 41}{space 1}    1.80{col 50}{space 3}0.072{col 58}{space 4}-.0057962{col 71}{space 3} .1376273
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .098049{col 30}{space 2} .0237223{col 41}{space 1}    4.13{col 50}{space 3}0.000{col 58}{space 4} .0515541{col 71}{space 3} .1445439
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1894087{col 30}{space 2} .0199555{col 41}{space 1}    9.49{col 50}{space 3}0.000{col 58}{space 4} .1502967{col 71}{space 3} .2285208
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0002662{col 30}{space 2} .0202413{col 41}{space 1}    0.01{col 50}{space 3}0.990{col 58}{space 4} -.039406{col 71}{space 3} .0399384
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005855{col 30}{space 2} .0011072{col 41}{space 1}    0.53{col 50}{space 3}0.597{col 58}{space 4}-.0015845{col 71}{space 3} .0027555
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1467062{col 30}{space 2} .0162753{col 41}{space 1}    9.01{col 50}{space 3}0.000{col 58}{space 4} .1148071{col 71}{space 3} .1786053
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0734636{col 30}{space 2} .0426087{col 41}{space 1}    1.72{col 50}{space 3}0.085{col 58}{space 4} -.010048{col 71}{space 3} .1569752
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5318315{col 30}{space 2} .0293683{col 41}{space 1}   18.11{col 50}{space 3}0.000{col 58}{space 4} .4742708{col 71}{space 3} .5893922
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6199591{col 30}{space 2} .0333418{col 41}{space 1}   18.59{col 50}{space 3}0.000{col 58}{space 4} .5546103{col 71}{space 3} .6853078
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1153848{col 30}{space 2} .0319646{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .0527353{col 71}{space 3} .1780342
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1631456{col 30}{space 2} .0270996{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4} .1100313{col 71}{space 3} .2162599
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2463019{col 30}{space 2} .0721977{col 41}{space 1}    3.41{col 50}{space 3}0.001{col 58}{space 4}  .104797{col 71}{space 3} .3878067
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1112935{col 30}{space 2} .0105877{col 41}{space 1}   10.51{col 50}{space 3}0.000{col 58}{space 4}  .090542{col 71}{space 3} .1320449
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3316184{col 30}{space 2}  .037988{col 41}{space 1}   -8.73{col 50}{space 3}0.000{col 58}{space 4}-.4060736{col 71}{space 3}-.2571632
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.572511{col 30}{space 2} .0369126{col 41}{space 1}  -42.60{col 50}{space 3}0.000{col 58}{space 4}-1.644858{col 71}{space 3}-1.500163
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4729246{col 30}{space 2} .0381221{col 41}{space 1}  -12.41{col 50}{space 3}0.000{col 58}{space 4}-.5476426{col 71}{space 3}-.3982066
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3045456{col 30}{space 2} .0376524{col 41}{space 1}   -8.09{col 50}{space 3}0.000{col 58}{space 4}-.3783429{col 71}{space 3}-.2307482
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2974959{col 30}{space 2} .0471485{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .2050865{col 71}{space 3} .3899052
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.244342{col 30}{space 2} .0477207{col 41}{space 1}   -5.12{col 50}{space 3}0.000{col 58}{space 4}-.3378729{col 71}{space 3}-.1508111
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0223268{col 30}{space 2} .0360931{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.0484145{col 71}{space 3} .0930681
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0286426{col 30}{space 2} .0404822{col 41}{space 1}    0.71{col 50}{space 3}0.479{col 58}{space 4} -.050701{col 71}{space 3} .1079862
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0138249{col 30}{space 2} .0368049{col 41}{space 1}    0.38{col 50}{space 3}0.707{col 58}{space 4}-.0583113{col 71}{space 3} .0859611
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1185134{col 30}{space 2} .0408734{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0384031{col 71}{space 3} .1986238
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1167097{col 30}{space 2} .0414943{col 41}{space 1}   -2.81{col 50}{space 3}0.005{col 58}{space 4}-.1980371{col 71}{space 3}-.0353823
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1792599{col 30}{space 2} .0398241{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1012062{col 71}{space 3} .2573137
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} -.199083{col 30}{space 2}  .061504{col 41}{space 1}   -3.24{col 50}{space 3}0.001{col 58}{space 4}-.3196286{col 71}{space 3}-.0785374
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4684488{col 30}{space 2} .0448863{col 41}{space 1}   10.44{col 50}{space 3}0.000{col 58}{space 4} .3804734{col 71}{space 3} .5564242
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0368538{col 30}{space 2} .0426003{col 41}{space 1}    0.87{col 50}{space 3}0.387{col 58}{space 4}-.0466413{col 71}{space 3} .1203488
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 3.871475{col 30}{space 2} .0749891{col 41}{space 1}   51.63{col 50}{space 3}0.000{col 58}{space 4} 3.724499{col 71}{space 3} 4.018451
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78504384
         {txt}sigma_e {c |} {res} 1.2263999
             {txt}rho {c |} {res} .29065657{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0199                                         {txt}min = {res}         1
{txt}     between = {res}0.3146                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2046                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1916.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0585001{col 30}{space 2} .0174819{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0242361{col 71}{space 3}  .092764
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0058975{col 30}{space 2} .0006369{col 41}{space 1}   -9.26{col 50}{space 3}0.000{col 58}{space 4}-.0071458{col 71}{space 3}-.0046491
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0508569{col 30}{space 2} .0075018{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4} .0361536{col 71}{space 3} .0655603
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.019247{col 30}{space 2} .0675593{col 41}{space 1}   -0.28{col 50}{space 3}0.776{col 58}{space 4}-.1516608{col 71}{space 3} .1131668
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0021189{col 30}{space 2} .0011566{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.0043858{col 71}{space 3}  .000148
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0559353{col 30}{space 2} .0439129{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4} -.142003{col 71}{space 3} .0301324
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3130442{col 30}{space 2} .0334877{col 41}{space 1}    9.35{col 50}{space 3}0.000{col 58}{space 4} .2474095{col 71}{space 3}  .378679
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} -.202492{col 30}{space 2} .1635002{col 41}{space 1}   -1.24{col 50}{space 3}0.216{col 58}{space 4}-.5229465{col 71}{space 3} .1179624
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1691596{col 30}{space 2} .0396155{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0915147{col 71}{space 3} .2468045
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1382673{col 30}{space 2} .0691233{col 41}{space 1}    2.00{col 50}{space 3}0.045{col 58}{space 4} .0027881{col 71}{space 3} .2737464
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0954523{col 30}{space 2} .0783797{col 41}{space 1}    1.22{col 50}{space 3}0.223{col 58}{space 4}-.0581691{col 71}{space 3} .2490736
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1969611{col 30}{space 2} .0535487{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0920076{col 71}{space 3} .3019146
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1133945{col 30}{space 2}  .042186{col 41}{space 1}   -2.69{col 50}{space 3}0.007{col 58}{space 4}-.1960776{col 71}{space 3}-.0307113
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0135088{col 30}{space 2} .0037589{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .0061416{col 71}{space 3} .0208761
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2619316{col 30}{space 2} .0318019{col 41}{space 1}    8.24{col 50}{space 3}0.000{col 58}{space 4}  .199601{col 71}{space 3} .3242621
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .8245051{col 30}{space 2} .2736106{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .2882382{col 71}{space 3} 1.360772
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4298442{col 30}{space 2} .0591408{col 41}{space 1}    7.27{col 50}{space 3}0.000{col 58}{space 4} .3139304{col 71}{space 3} .5457579
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4345767{col 30}{space 2} .0729522{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .2915929{col 71}{space 3} .5775604
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3169809{col 30}{space 2} .1150559{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} .0914754{col 71}{space 3} .5424864
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1399173{col 30}{space 2} .0669874{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0086244{col 71}{space 3} .2712102
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .0609759{col 30}{space 2} .1600361{col 41}{space 1}    0.38{col 50}{space 3}0.703{col 58}{space 4}-.2526891{col 71}{space 3} .3746408
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0754629{col 30}{space 2} .0215934{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .0331407{col 71}{space 3} .1177851
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1573534{col 30}{space 2} .0229874{col 41}{space 1}   -6.85{col 50}{space 3}0.000{col 58}{space 4}-.2024079{col 71}{space 3}-.1122989
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.570474{col 30}{space 2} .1206822{col 41}{space 1}   21.30{col 50}{space 3}0.000{col 58}{space 4} 2.333941{col 71}{space 3} 2.807006
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69610925
         {txt}sigma_e {c |} {res}  1.055726
             {txt}rho {c |} {res} .30302067{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0213                                         {txt}min = {res}         1
{txt}     between = {res}0.3875                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2479                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1234.99
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0162004{col 30}{space 2}  .029212{col 41}{space 1}    0.55{col 50}{space 3}0.579{col 58}{space 4} -.041054{col 71}{space 3} .0734548
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0150642{col 30}{space 2} .0037184{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.0223521{col 71}{space 3}-.0077762
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0038641{col 30}{space 2} .0118854{col 41}{space 1}   -0.33{col 50}{space 3}0.745{col 58}{space 4} -.027159{col 71}{space 3} .0194309
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2589378{col 30}{space 2} .1189801{col 41}{space 1}   -2.18{col 50}{space 3}0.030{col 58}{space 4}-.4921345{col 71}{space 3}-.0257411
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0030802{col 30}{space 2} .0019125{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-.0068286{col 71}{space 3} .0006682
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0301203{col 30}{space 2} .0718534{col 41}{space 1}   -0.42{col 50}{space 3}0.675{col 58}{space 4}-.1709503{col 71}{space 3} .1107097
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3457785{col 30}{space 2} .0629114{col 41}{space 1}    5.50{col 50}{space 3}0.000{col 58}{space 4} .2224745{col 71}{space 3} .4690826
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .237004{col 30}{space 2} .2181379{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.1905385{col 71}{space 3} .6645464
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1648957{col 30}{space 2} .0763467{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0152588{col 71}{space 3} .3145325
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4402989{col 30}{space 2} .1986718{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0509092{col 71}{space 3} .8296885
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1896299{col 30}{space 2} .0961995{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0010824{col 71}{space 3} .3781774
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2739993{col 30}{space 2} .0620001{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1524814{col 71}{space 3} .3955173
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2567918{col 30}{space 2} .0680876{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.3902412{col 71}{space 3}-.1233425
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0853082{col 30}{space 2} .0347569{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0171858{col 71}{space 3} .1534306
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0899618{col 30}{space 2} .0625237{col 41}{space 1}    1.44{col 50}{space 3}0.150{col 58}{space 4}-.0325824{col 71}{space 3}  .212506
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1246431{col 30}{space 2} .3303792{col 41}{space 1}    0.38{col 50}{space 3}0.706{col 58}{space 4}-.5228883{col 71}{space 3} .7721745
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6703289{col 30}{space 2} .1161163{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .4427451{col 71}{space 3} .8979128
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8965259{col 30}{space 2} .2232185{col 41}{space 1}    4.02{col 50}{space 3}0.000{col 58}{space 4} .4590256{col 71}{space 3} 1.334026
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4228674{col 30}{space 2} .1298963{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .1682754{col 71}{space 3} .6774595
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3461454{col 30}{space 2} .1089665{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4}  .132575{col 71}{space 3} .5597158
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.5540795{col 30}{space 2} .2676719{col 41}{space 1}   -2.07{col 50}{space 3}0.038{col 58}{space 4}-1.078707{col 71}{space 3}-.0294522
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0288691{col 30}{space 2} .0456344{col 41}{space 1}   -0.63{col 50}{space 3}0.527{col 58}{space 4} -.118311{col 71}{space 3} .0605727
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .313474{col 30}{space 2} .0638211{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4} .1883868{col 71}{space 3} .4385611
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .147181{col 30}{space 2}  .055366{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0386656{col 71}{space 3} .2556964
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  5.51704{col 30}{space 2} .2828416{col 41}{space 1}   19.51{col 50}{space 3}0.000{col 58}{space 4}  4.96268{col 71}{space 3} 6.071399
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72745881
         {txt}sigma_e {c |} {res} 1.2971485
             {txt}rho {c |} {res} .23926148{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0367                                         {txt}min = {res}         1
{txt}     between = {res}0.1780                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1336                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}   905.81
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .1135618{col 30}{space 2} .0391586{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0368124{col 71}{space 3} .1903111
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.001748{col 30}{space 2} .0003421{col 41}{space 1}   -5.11{col 50}{space 3}0.000{col 58}{space 4}-.0024184{col 71}{space 3}-.0010775
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0115384{col 30}{space 2} .0071379{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0024516{col 71}{space 3} .0255285
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0145664{col 30}{space 2} .1329438{col 41}{space 1}   -0.11{col 50}{space 3}0.913{col 58}{space 4}-.2751314{col 71}{space 3} .2459986
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0050811{col 30}{space 2} .0019151{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0013276{col 71}{space 3} .0088347
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0004075{col 30}{space 2} .0856266{col 41}{space 1}   -0.00{col 50}{space 3}0.996{col 58}{space 4}-.1682326{col 71}{space 3} .1674176
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2723717{col 30}{space 2}  .058672{col 41}{space 1}    4.64{col 50}{space 3}0.000{col 58}{space 4} .1573767{col 71}{space 3} .3873666
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .5123626{col 30}{space 2} .1546523{col 41}{space 1}    3.31{col 50}{space 3}0.001{col 58}{space 4} .2092497{col 71}{space 3} .8154755
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0472744{col 30}{space 2} .0898095{col 41}{space 1}    0.53{col 50}{space 3}0.599{col 58}{space 4} -.128749{col 71}{space 3} .2232978
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0271251{col 30}{space 2} .2386065{col 41}{space 1}   -0.11{col 50}{space 3}0.909{col 58}{space 4}-.4947852{col 71}{space 3}  .440535
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2133177{col 30}{space 2}  .119957{col 41}{space 1}    1.78{col 50}{space 3}0.075{col 58}{space 4}-.0217936{col 71}{space 3} .4484291
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2368695{col 30}{space 2} .0807258{col 41}{space 1}   -2.93{col 50}{space 3}0.003{col 58}{space 4}-.3950892{col 71}{space 3}-.0786498
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0433238{col 30}{space 2}  .077686{col 41}{space 1}   -0.56{col 50}{space 3}0.577{col 58}{space 4}-.1955856{col 71}{space 3} .1089379
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012693{col 30}{space 2} .0015408{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.0042893{col 71}{space 3} .0017506
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2387342{col 30}{space 2} .2154452{col 41}{space 1}    1.11{col 50}{space 3}0.268{col 58}{space 4}-.1835306{col 71}{space 3} .6609989
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0443192{col 30}{space 2} .1742175{col 41}{space 1}   -0.25{col 50}{space 3}0.799{col 58}{space 4}-.3857793{col 71}{space 3} .2971409
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2634283{col 30}{space 2} .1045144{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0585839{col 71}{space 3} .4682727
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6851661{col 30}{space 2} .1972425{col 41}{space 1}    3.47{col 50}{space 3}0.001{col 58}{space 4} .2985778{col 71}{space 3} 1.071754
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0188007{col 30}{space 2} .1352553{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4}-.2838962{col 71}{space 3} .2462949
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4530907{col 30}{space 2} .0953477{col 41}{space 1}    4.75{col 50}{space 3}0.000{col 58}{space 4} .2662126{col 71}{space 3} .6399687
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .4066581{col 30}{space 2} .3231017{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.2266095{col 71}{space 3} 1.039926
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0431941{col 30}{space 2} .0459752{col 41}{space 1}    0.94{col 50}{space 3}0.347{col 58}{space 4}-.0469157{col 71}{space 3} .1333039
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2461971{col 30}{space 2} .0475165{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4} .1530665{col 71}{space 3} .3393277
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.593699{col 30}{space 2} .2081887{col 41}{space 1}   17.26{col 50}{space 3}0.000{col 58}{space 4} 3.185657{col 71}{space 3} 4.001742
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50920376
         {txt}sigma_e {c |} {res} 1.4277919
             {txt}rho {c |} {res} .11283822{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0354                                         {txt}min = {res}         1
{txt}     between = {res}0.3134                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2661                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  3768.74
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0567075{col 30}{space 2} .0176579{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0220986{col 71}{space 3} .0913164
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0186506{col 30}{space 2} .0026708{col 41}{space 1}   -6.98{col 50}{space 3}0.000{col 58}{space 4}-.0238853{col 71}{space 3}-.0134158
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0258993{col 30}{space 2} .0049186{col 41}{space 1}   -5.27{col 50}{space 3}0.000{col 58}{space 4}-.0355396{col 71}{space 3} -.016259
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2483665{col 30}{space 2} .0692485{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4}  .112642{col 71}{space 3}  .384091
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0058927{col 30}{space 2}  .001215{col 41}{space 1}    4.85{col 50}{space 3}0.000{col 58}{space 4} .0035113{col 71}{space 3}  .008274
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2333762{col 30}{space 2} .0526054{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .1302715{col 71}{space 3}  .336481
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1619742{col 30}{space 2}  .032663{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0979559{col 71}{space 3} .2259925
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0357849{col 30}{space 2} .0524383{col 41}{space 1}    0.68{col 50}{space 3}0.495{col 58}{space 4}-.0669923{col 71}{space 3}  .138562
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1211602{col 30}{space 2}  .046085{col 41}{space 1}    2.63{col 50}{space 3}0.009{col 58}{space 4} .0308353{col 71}{space 3} .2114851
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0836443{col 30}{space 2}  .091382{col 41}{space 1}   -0.92{col 50}{space 3}0.360{col 58}{space 4}-.2627498{col 71}{space 3} .0954612
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1702357{col 30}{space 2} .0747366{col 41}{space 1}    2.28{col 50}{space 3}0.023{col 58}{space 4} .0237548{col 71}{space 3} .3167167
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2818429{col 30}{space 2} .0492659{col 41}{space 1}    5.72{col 50}{space 3}0.000{col 58}{space 4} .1852836{col 71}{space 3} .3784023
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1408964{col 30}{space 2} .0581372{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0269496{col 71}{space 3} .2548432
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.004502{col 30}{space 2} .0059405{col 41}{space 1}   -0.76{col 50}{space 3}0.449{col 58}{space 4}-.0161453{col 71}{space 3} .0071412
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3296726{col 30}{space 2} .0609087{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .2102938{col 71}{space 3} .4490514
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1153621{col 30}{space 2} .0603904{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0030009{col 71}{space 3} .2337251
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7081911{col 30}{space 2} .0634265{col 41}{space 1}   11.17{col 50}{space 3}0.000{col 58}{space 4} .5838774{col 71}{space 3} .8325049
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8195967{col 30}{space 2} .0684724{col 41}{space 1}   11.97{col 50}{space 3}0.000{col 58}{space 4} .6853933{col 71}{space 3}    .9538
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1428509{col 30}{space 2}  .084919{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0235872{col 71}{space 3}  .309289
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0379818{col 30}{space 2} .0591491{col 41}{space 1}   -0.64{col 50}{space 3}0.521{col 58}{space 4}-.1539118{col 71}{space 3} .0779483
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3274892{col 30}{space 2} .1576353{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0185298{col 71}{space 3} .6364487
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1462464{col 30}{space 2} .0223083{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4}  .102523{col 71}{space 3} .1899698
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6068926{col 30}{space 2} .0539303{col 41}{space 1}  -11.25{col 50}{space 3}0.000{col 58}{space 4} -.712594{col 71}{space 3}-.5011913
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.583821{col 30}{space 2} .0525191{col 41}{space 1}  -11.12{col 50}{space 3}0.000{col 58}{space 4}-.6867565{col 71}{space 3}-.4808856
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4239081{col 30}{space 2} .0491092{col 41}{space 1}   -8.63{col 50}{space 3}0.000{col 58}{space 4}-.5201604{col 71}{space 3}-.3276558
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.773952{col 30}{space 2} .1084276{col 41}{space 1}   34.81{col 50}{space 3}0.000{col 58}{space 4} 3.561438{col 71}{space 3} 3.986466
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .82146131
         {txt}sigma_e {c |} {res} 1.2205785
             {txt}rho {c |} {res}  .3117414{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0138                                         {txt}min = {res}         1
{txt}     between = {res}0.2249                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1673                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1633.89
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .010564{col 30}{space 2} .0227274{col 41}{space 1}    0.46{col 50}{space 3}0.642{col 58}{space 4}-.0339808{col 71}{space 3} .0551088
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0153269{col 30}{space 2} .0048673{col 41}{space 1}   -3.15{col 50}{space 3}0.002{col 58}{space 4}-.0248666{col 71}{space 3}-.0057872
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0020561{col 30}{space 2} .0054419{col 41}{space 1}   -0.38{col 50}{space 3}0.706{col 58}{space 4}-.0127221{col 71}{space 3} .0086099
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .2154503{col 30}{space 2} .0768851{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0647583{col 71}{space 3} .3661423
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}   .00359{col 30}{space 2} .0012596{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0011212{col 71}{space 3} .0060588
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1814153{col 30}{space 2} .0475073{col 41}{space 1}   -3.82{col 50}{space 3}0.000{col 58}{space 4}-.2745279{col 71}{space 3}-.0883026
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1694774{col 30}{space 2} .0384551{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0941067{col 71}{space 3}  .244848
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4410112{col 30}{space 2} .0972211{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .2504614{col 71}{space 3}  .631561
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1964382{col 30}{space 2} .0513614{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .0957718{col 71}{space 3} .2971046
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3985659{col 30}{space 2} .0821074{col 41}{space 1}   -4.85{col 50}{space 3}0.000{col 58}{space 4}-.5594934{col 71}{space 3}-.2376385
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0516827{col 30}{space 2} .0486961{col 41}{space 1}   -1.06{col 50}{space 3}0.289{col 58}{space 4}-.1471254{col 71}{space 3}   .04376
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1089602{col 30}{space 2} .0449384{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0208826{col 71}{space 3} .1970378
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1410673{col 30}{space 2} .0536041{col 41}{space 1}    2.63{col 50}{space 3}0.008{col 58}{space 4} .0360052{col 71}{space 3} .2461294
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0037075{col 30}{space 2} .0030763{col 41}{space 1}    1.21{col 50}{space 3}0.228{col 58}{space 4}-.0023219{col 71}{space 3} .0097369
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .149709{col 30}{space 2} .0328415{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .0853408{col 71}{space 3} .2140772
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3168546{col 30}{space 2} .1221182{col 41}{space 1}    2.59{col 50}{space 3}0.009{col 58}{space 4} .0775073{col 71}{space 3} .5562019
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4210473{col 30}{space 2} .0686266{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .2865418{col 71}{space 3} .5555529
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3958972{col 30}{space 2} .0809774{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .2371844{col 71}{space 3}   .55461
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0583797{col 30}{space 2} .0579348{col 41}{space 1}   -1.01{col 50}{space 3}0.314{col 58}{space 4}-.1719299{col 71}{space 3} .0551704
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2760124{col 30}{space 2} .0600024{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4}   .15841{col 71}{space 3} .3936149
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.188162{col 30}{space 2} .1596894{col 41}{space 1}    7.44{col 50}{space 3}0.000{col 58}{space 4} .8751766{col 71}{space 3} 1.501148
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0079038{col 30}{space 2} .0274787{col 41}{space 1}    0.29{col 50}{space 3}0.774{col 58}{space 4}-.0459534{col 71}{space 3} .0617611
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0772769{col 30}{space 2} .0404169{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4}-.1564926{col 71}{space 3} .0019389
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.001495{col 30}{space 2} .0346761{col 41}{space 1}   -0.04{col 50}{space 3}0.966{col 58}{space 4}-.0694589{col 71}{space 3}  .066469
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1381978{col 30}{space 2} .0433788{col 41}{space 1}   -3.19{col 50}{space 3}0.001{col 58}{space 4}-.2232186{col 71}{space 3} -.053177
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.322637{col 30}{space 2} .1368973{col 41}{space 1}   31.58{col 50}{space 3}0.000{col 58}{space 4} 4.054323{col 71}{space 3}  4.59095
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .74633936
         {txt}sigma_e {c |} {res} 1.2122088
             {txt}rho {c |} {res} .27487293{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0461                                         {txt}min = {res}         1
{txt}     between = {res}0.2927                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1904                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}  2322.19
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0235044{col 30}{space 2} .0145366{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0049868{col 71}{space 3} .0519957
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0192758{col 30}{space 2} .0031897{col 41}{space 1}   -6.04{col 50}{space 3}0.000{col 58}{space 4}-.0255276{col 71}{space 3} -.013024
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0180661{col 30}{space 2} .0056166{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0070578{col 71}{space 3} .0290744
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1399398{col 30}{space 2} .0647846{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.2669152{col 71}{space 3}-.0129643
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023835{col 30}{space 2} .0011337{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0046055{col 71}{space 3}-.0001616
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1475821{col 30}{space 2}  .039382{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0703949{col 71}{space 3} .2247694
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3892704{col 30}{space 2}  .035829{col 41}{space 1}   10.86{col 50}{space 3}0.000{col 58}{space 4} .3190468{col 71}{space 3} .4594941
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1024355{col 30}{space 2} .0610206{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0171627{col 71}{space 3} .2220336
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .272478{col 30}{space 2} .0385836{col 41}{space 1}    7.06{col 50}{space 3}0.000{col 58}{space 4} .1968555{col 71}{space 3} .3481006
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5838045{col 30}{space 2} .0528935{col 41}{space 1}   11.04{col 50}{space 3}0.000{col 58}{space 4} .4801351{col 71}{space 3}  .687474
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1399105{col 30}{space 2} .0352427{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .0708362{col 71}{space 3} .2089849
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2563398{col 30}{space 2} .0341287{col 41}{space 1}    7.51{col 50}{space 3}0.000{col 58}{space 4} .1894487{col 71}{space 3} .3232309
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1249571{col 30}{space 2} .0329488{col 41}{space 1}   -3.79{col 50}{space 3}0.000{col 58}{space 4}-.1895356{col 71}{space 3}-.0603786
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0023499{col 30}{space 2} .0017657{col 41}{space 1}    1.33{col 50}{space 3}0.183{col 58}{space 4}-.0011107{col 71}{space 3} .0058106
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0272087{col 30}{space 2} .0278924{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0274594{col 71}{space 3} .0818769
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1730459{col 30}{space 2} .0885063{col 41}{space 1}    1.96{col 50}{space 3}0.051{col 58}{space 4}-.0004233{col 71}{space 3}  .346515
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3569307{col 30}{space 2} .0636993{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .2320823{col 71}{space 3} .4817791
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3031786{col 30}{space 2} .0729909{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4}  .160119{col 71}{space 3} .4462381
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1452409{col 30}{space 2} .0574984{col 41}{space 1}    2.53{col 50}{space 3}0.012{col 58}{space 4} .0325462{col 71}{space 3} .2579356
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2901631{col 30}{space 2} .0555402{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4} .1813063{col 71}{space 3} .3990199
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.8185143{col 30}{space 2} .1334437{col 41}{space 1}   -6.13{col 50}{space 3}0.000{col 58}{space 4}-1.080059{col 71}{space 3}-.5569695
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .227844{col 30}{space 2} .0243472{col 41}{space 1}    9.36{col 50}{space 3}0.000{col 58}{space 4} .1801243{col 71}{space 3} .2755637
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1236864{col 30}{space 2} .0401867{col 41}{space 1}   -3.08{col 50}{space 3}0.002{col 58}{space 4}-.2024509{col 71}{space 3}-.0449219
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0131421{col 30}{space 2} .0375919{col 41}{space 1}    0.35{col 50}{space 3}0.727{col 58}{space 4}-.0605368{col 71}{space 3} .0868209
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .383679{col 30}{space 2} .0357741{col 41}{space 1}   10.73{col 50}{space 3}0.000{col 58}{space 4} .3135631{col 71}{space 3} .4537949
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}  .138244{col 30}{space 2} .0359831{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0677185{col 71}{space 3} .2087696
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2295732{col 30}{space 2} .0345209{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .1619135{col 71}{space 3} .2972328
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.146477{col 30}{space 2}  .146674{col 41}{space 1}   21.45{col 50}{space 3}0.000{col 58}{space 4} 2.859001{col 71}{space 3} 3.433952
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .75645347
         {txt}sigma_e {c |} {res} 1.2472747
             {txt}rho {c |} {res} .26891186{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S17_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town _cons)
{res}{txt}(note: file S17_farmer_imr.rtf not found)
(output written to {browse  `"S17_farmer_imr.rtf"'})

{com}. 
. 
. 
. 
. *                          dist_village_level                                  *
. 
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    57,175
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    23,508

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0230                                         {txt}min = {res}         1
{txt}     between = {res}0.3557                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2697                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}37{txt})     =  {res} 16619.76
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:23,508} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0278038{col 30}{space 2}  .009599{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0089901{col 71}{space 3} .0466176
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0015688{col 30}{space 2} .0001929{col 41}{space 1}   -8.13{col 50}{space 3}0.000{col 58}{space 4}-.0019468{col 71}{space 3}-.0011908
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0014865{col 30}{space 2} .0025797{col 41}{space 1}   -0.58{col 50}{space 3}0.564{col 58}{space 4}-.0065426{col 71}{space 3} .0035697
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0492331{col 30}{space 2} .0328745{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0151996{col 71}{space 3} .1136659
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0020619{col 30}{space 2} .0005454{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4}  .000993{col 71}{space 3} .0031308
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0010182{col 30}{space 2} .0213607{col 41}{space 1}    0.05{col 50}{space 3}0.962{col 58}{space 4}-.0408481{col 71}{space 3} .0428845
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2822885{col 30}{space 2} .0163964{col 41}{space 1}   17.22{col 50}{space 3}0.000{col 58}{space 4} .2501521{col 71}{space 3} .3144248
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1407642{col 30}{space 2} .0339094{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4}  .074303{col 71}{space 3} .2072253
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1543699{col 30}{space 2} .0208926{col 41}{space 1}    7.39{col 50}{space 3}0.000{col 58}{space 4} .1134211{col 71}{space 3} .1953186
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0738798{col 30}{space 2} .0366242{col 41}{space 1}    2.02{col 50}{space 3}0.044{col 58}{space 4} .0020978{col 71}{space 3} .1456618
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1015033{col 30}{space 2} .0237473{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0549595{col 71}{space 3} .1480471
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1904394{col 30}{space 2} .0199564{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .1513255{col 71}{space 3} .2295532
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0030624{col 30}{space 2} .0202931{col 41}{space 1}   -0.15{col 50}{space 3}0.880{col 58}{space 4}-.0428362{col 71}{space 3} .0367114
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0009357{col 30}{space 2} .0011071{col 41}{space 1}    0.85{col 50}{space 3}0.398{col 58}{space 4}-.0012342{col 71}{space 3} .0031057
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1637305{col 30}{space 2} .0163161{col 41}{space 1}   10.03{col 50}{space 3}0.000{col 58}{space 4} .1317515{col 71}{space 3} .1957095
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0864537{col 30}{space 2} .0427429{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0026791{col 71}{space 3} .1702282
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5335785{col 30}{space 2} .0294367{col 41}{space 1}   18.13{col 50}{space 3}0.000{col 58}{space 4} .4758836{col 71}{space 3} .5912733
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5937757{col 30}{space 2} .0334124{col 41}{space 1}   17.77{col 50}{space 3}0.000{col 58}{space 4} .5282887{col 71}{space 3} .6592627
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1043856{col 30}{space 2}  .032034{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0416001{col 71}{space 3} .1671711
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1466386{col 30}{space 2} .0271993{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0933289{col 71}{space 3} .1999482
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .2249608{col 30}{space 2} .0723543{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4} .0831491{col 71}{space 3} .3667726
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0957948{col 30}{space 2} .0127963{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .0707144{col 71}{space 3} .1208751
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4351034{col 30}{space 2}  .036163{col 41}{space 1}  -12.03{col 50}{space 3}0.000{col 58}{space 4}-.5059817{col 71}{space 3}-.3642252
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.529647{col 30}{space 2} .0400723{col 41}{space 1}  -38.17{col 50}{space 3}0.000{col 58}{space 4}-1.608187{col 71}{space 3}-1.451106
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5070789{col 30}{space 2} .0404584{col 41}{space 1}  -12.53{col 50}{space 3}0.000{col 58}{space 4}-.5863759{col 71}{space 3}-.4277818
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3354136{col 30}{space 2} .0401491{col 41}{space 1}   -8.35{col 50}{space 3}0.000{col 58}{space 4}-.4141044{col 71}{space 3}-.2567228
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3164344{col 30}{space 2}  .047651{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .2230401{col 71}{space 3} .4098287
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2441644{col 30}{space 2} .0476764{col 41}{space 1}   -5.12{col 50}{space 3}0.000{col 58}{space 4}-.3376084{col 71}{space 3}-.1507203
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0318372{col 30}{space 2} .0360809{col 41}{space 1}    0.88{col 50}{space 3}0.378{col 58}{space 4}-.0388801{col 71}{space 3} .1025544
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0454737{col 30}{space 2} .0404326{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.0337727{col 71}{space 3} .1247201
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0240717{col 30}{space 2} .0368216{col 41}{space 1}    0.65{col 50}{space 3}0.513{col 58}{space 4}-.0480972{col 71}{space 3} .0962406
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1326595{col 30}{space 2} .0408749{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .0525462{col 71}{space 3} .2127728
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1071548{col 30}{space 2} .0413779{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4} -.188254{col 71}{space 3}-.0260555
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1921056{col 30}{space 2} .0397836{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .1141311{col 71}{space 3}   .27008
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1964544{col 30}{space 2} .0614533{col 41}{space 1}   -3.20{col 50}{space 3}0.001{col 58}{space 4}-.3169007{col 71}{space 3}-.0760081
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4789175{col 30}{space 2} .0451382{col 41}{space 1}   10.61{col 50}{space 3}0.000{col 58}{space 4} .3904482{col 71}{space 3} .5673868
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0442112{col 30}{space 2} .0425908{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.0392652{col 71}{space 3} .1276876
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 3.885387{col 30}{space 2} .0853066{col 41}{space 1}   45.55{col 50}{space 3}0.000{col 58}{space 4} 3.718189{col 71}{space 3} 4.052585
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79136282
         {txt}sigma_e {c |} {res} 1.2265625
             {txt}rho {c |} {res} .29391842{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,949
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,810

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0198                                         {txt}min = {res}         1
{txt}     between = {res}0.3130                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.2036                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1897.78
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,810} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}  .064269{col 30}{space 2} .0177281{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4} .0295226{col 71}{space 3} .0990155
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0054432{col 30}{space 2} .0006416{col 41}{space 1}   -8.48{col 50}{space 3}0.000{col 58}{space 4}-.0067007{col 71}{space 3}-.0041857
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0509224{col 30}{space 2} .0075047{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .0362136{col 71}{space 3} .0656313
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0132788{col 30}{space 2} .0676311{col 41}{space 1}   -0.20{col 50}{space 3}0.844{col 58}{space 4}-.1458333{col 71}{space 3} .1192757
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.002314{col 30}{space 2} .0011593{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4}-.0045861{col 71}{space 3}-.0000418
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0568979{col 30}{space 2} .0439476{col 41}{space 1}   -1.29{col 50}{space 3}0.195{col 58}{space 4}-.1430336{col 71}{space 3} .0292378
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3142251{col 30}{space 2} .0335055{col 41}{space 1}    9.38{col 50}{space 3}0.000{col 58}{space 4} .2485556{col 71}{space 3} .3798947
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2051273{col 30}{space 2} .1637604{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.5260918{col 71}{space 3} .1158372
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1693198{col 30}{space 2} .0396059{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0916938{col 71}{space 3} .2469459
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1370252{col 30}{space 2} .0691896{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0014161{col 71}{space 3} .2726344
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0943702{col 30}{space 2} .0784121{col 41}{space 1}    1.20{col 50}{space 3}0.229{col 58}{space 4}-.0593147{col 71}{space 3} .2480551
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1961092{col 30}{space 2} .0535714{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .0911113{col 71}{space 3} .3011071
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1147237{col 30}{space 2} .0422498{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-.1975318{col 71}{space 3}-.0319157
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0139845{col 30}{space 2} .0037922{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .0065519{col 71}{space 3} .0214171
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2675902{col 30}{space 2}  .031658{col 41}{space 1}    8.45{col 50}{space 3}0.000{col 58}{space 4} .2055416{col 71}{space 3} .3296387
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .8533603{col 30}{space 2} .2736483{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .3170194{col 71}{space 3} 1.389701
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4270855{col 30}{space 2} .0591928{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .3110697{col 71}{space 3} .5431013
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4055056{col 30}{space 2} .0730115{col 41}{space 1}    5.55{col 50}{space 3}0.000{col 58}{space 4} .2624056{col 71}{space 3} .5486055
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .307695{col 30}{space 2} .1153333{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0816459{col 71}{space 3} .5337441
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1289879{col 30}{space 2} .0671247{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0025741{col 71}{space 3} .2605498
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .0637487{col 30}{space 2} .1603247{col 41}{space 1}    0.40{col 50}{space 3}0.691{col 58}{space 4} -.250482{col 71}{space 3} .3779794
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0672276{col 30}{space 2} .0219751{col 41}{space 1}    3.06{col 50}{space 3}0.002{col 58}{space 4} .0241573{col 71}{space 3} .1102979
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1585906{col 30}{space 2} .0230215{col 41}{space 1}   -6.89{col 50}{space 3}0.000{col 58}{space 4}-.2037118{col 71}{space 3}-.1134693
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.587596{col 30}{space 2} .1223868{col 41}{space 1}   21.14{col 50}{space 3}0.000{col 58}{space 4} 2.347722{col 71}{space 3} 2.827469
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69755929
         {txt}sigma_e {c |} {res} 1.0556563
             {txt}rho {c |} {res} .30392831{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,125
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,370

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0227                                         {txt}min = {res}         1
{txt}     between = {res}0.3902                                         {txt}avg = {res}       3.0
{txt}     overall = {res}0.2494                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1229.29
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,370} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0676156{col 30}{space 2} .0438842{col 41}{space 1}   -1.54{col 50}{space 3}0.123{col 58}{space 4} -.153627{col 71}{space 3} .0183957
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0042273{col 30}{space 2} .0011223{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.0064269{col 71}{space 3}-.0020277
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0043104{col 30}{space 2} .0119599{col 41}{space 1}   -0.36{col 50}{space 3}0.719{col 58}{space 4}-.0277515{col 71}{space 3} .0191306
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.259353{col 30}{space 2} .1191789{col 41}{space 1}   -2.18{col 50}{space 3}0.030{col 58}{space 4}-.4929394{col 71}{space 3}-.0257665
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0034714{col 30}{space 2}  .001912{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4}-.0072189{col 71}{space 3} .0002761
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0551033{col 30}{space 2} .0717484{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}-.1957276{col 71}{space 3}  .085521
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3260833{col 30}{space 2} .0630841{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .2024408{col 71}{space 3} .4497258
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2477736{col 30}{space 2} .2172383{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4}-.1780056{col 71}{space 3} .6735528
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .165081{col 30}{space 2} .0762745{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0155858{col 71}{space 3} .3145763
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4374189{col 30}{space 2} .1971459{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0510201{col 71}{space 3} .8238177
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1873879{col 30}{space 2}  .096286{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4}-.0013291{col 71}{space 3} .3761049
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2772434{col 30}{space 2} .0622358{col 41}{space 1}    4.45{col 50}{space 3}0.000{col 58}{space 4} .1552634{col 71}{space 3} .3992234
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2621463{col 30}{space 2} .0679698{col 41}{space 1}   -3.86{col 50}{space 3}0.000{col 58}{space 4}-.3953647{col 71}{space 3} -.128928
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .081147{col 30}{space 2} .0340644{col 41}{space 1}    2.38{col 50}{space 3}0.017{col 58}{space 4} .0143819{col 71}{space 3}  .147912
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .088695{col 30}{space 2} .0624256{col 41}{space 1}    1.42{col 50}{space 3}0.155{col 58}{space 4} -.033657{col 71}{space 3} .2110469
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0579849{col 30}{space 2} .3208884{col 41}{space 1}    0.18{col 50}{space 3}0.857{col 58}{space 4}-.5709448{col 71}{space 3} .6869146
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6800756{col 30}{space 2} .1152373{col 41}{space 1}    5.90{col 50}{space 3}0.000{col 58}{space 4} .4542147{col 71}{space 3} .9059366
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9737481{col 30}{space 2} .2196625{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .5432175{col 71}{space 3} 1.404279
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4234692{col 30}{space 2} .1294724{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .1697079{col 71}{space 3} .6772305
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3412486{col 30}{space 2} .1087248{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .1281519{col 71}{space 3} .5543453
{txt}{space 13}imr {c |}{col 18}{res}{space 2}-.5087462{col 30}{space 2} .2690449{col 41}{space 1}   -1.89{col 50}{space 3}0.059{col 58}{space 4}-1.036064{col 71}{space 3}  .018572
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0154212{col 30}{space 2}  .072711{col 41}{space 1}   -0.21{col 50}{space 3}0.832{col 58}{space 4}-.1579322{col 71}{space 3} .1270898
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2736252{col 30}{space 2} .0640541{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1480814{col 71}{space 3} .3991689
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1354961{col 30}{space 2} .0553245{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0270621{col 71}{space 3} .2439301
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 6.027578{col 30}{space 2} .4366396{col 41}{space 1}   13.80{col 50}{space 3}0.000{col 58}{space 4} 5.171781{col 71}{space 3} 6.883376
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72363531
         {txt}sigma_e {c |} {res} 1.2966214
             {txt}rho {c |} {res} .23749557{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     5,278
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,156

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0314                                         {txt}min = {res}         1
{txt}     between = {res}0.1774                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1290                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}   831.41
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,156} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0232317{col 30}{space 2} .0496465{col 41}{space 1}   -0.47{col 50}{space 3}0.640{col 58}{space 4} -.120537{col 71}{space 3} .0740736
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0000366{col 30}{space 2} .0003069{col 41}{space 1}    0.12{col 50}{space 3}0.905{col 58}{space 4}-.0005648{col 71}{space 3}  .000638
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0133236{col 30}{space 2} .0071592{col 41}{space 1}    1.86{col 50}{space 3}0.063{col 58}{space 4}-.0007082{col 71}{space 3} .0273554
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.013894{col 30}{space 2} .1337267{col 41}{space 1}   -0.10{col 50}{space 3}0.917{col 58}{space 4}-.2759935{col 71}{space 3} .2482055
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0045215{col 30}{space 2} .0019278{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4}  .000743{col 71}{space 3} .0082999
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0085191{col 30}{space 2} .0858484{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-.1767789{col 71}{space 3} .1597406
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2854365{col 30}{space 2} .0591515{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .1695016{col 71}{space 3} .4013714
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .5013719{col 30}{space 2} .1541717{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4} .1992008{col 71}{space 3} .8035429
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0547703{col 30}{space 2} .0901209{col 41}{space 1}    0.61{col 50}{space 3}0.543{col 58}{space 4}-.1218634{col 71}{space 3}  .231404
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0039479{col 30}{space 2} .2392293{col 41}{space 1}   -0.02{col 50}{space 3}0.987{col 58}{space 4}-.4728286{col 71}{space 3} .4649328
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2310529{col 30}{space 2} .1198737{col 41}{space 1}    1.93{col 50}{space 3}0.054{col 58}{space 4}-.0038951{col 71}{space 3}  .466001
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2167067{col 30}{space 2} .0807781{col 41}{space 1}   -2.68{col 50}{space 3}0.007{col 58}{space 4}-.3750289{col 71}{space 3}-.0583845
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0347855{col 30}{space 2} .0779924{col 41}{space 1}   -0.45{col 50}{space 3}0.656{col 58}{space 4}-.1876478{col 71}{space 3} .1180767
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0005742{col 30}{space 2} .0015331{col 41}{space 1}   -0.37{col 50}{space 3}0.708{col 58}{space 4} -.003579{col 71}{space 3} .0024306
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2373004{col 30}{space 2} .2157857{col 41}{space 1}    1.10{col 50}{space 3}0.271{col 58}{space 4}-.1856317{col 71}{space 3} .6602326
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0641702{col 30}{space 2} .1742613{col 41}{space 1}   -0.37{col 50}{space 3}0.713{col 58}{space 4}-.4057161{col 71}{space 3} .2773758
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2829658{col 30}{space 2} .1043526{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .0784385{col 71}{space 3} .4874931
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6395538{col 30}{space 2} .1971722{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .2531034{col 71}{space 3} 1.026004
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0144951{col 30}{space 2} .1352318{col 41}{space 1}   -0.11{col 50}{space 3}0.915{col 58}{space 4}-.2795445{col 71}{space 3} .2505543
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4471734{col 30}{space 2} .0955777{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4} .2598445{col 71}{space 3} .6345023
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3458742{col 30}{space 2} .3250494{col 41}{space 1}    1.06{col 50}{space 3}0.287{col 58}{space 4}-.2912109{col 71}{space 3} .9829593
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .1498307{col 30}{space 2} .0582811{col 41}{space 1}    2.57{col 50}{space 3}0.010{col 58}{space 4} .0356018{col 71}{space 3} .2640596
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2541041{col 30}{space 2} .0469704{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .1620437{col 71}{space 3} .3461644
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  3.52513{col 30}{space 2} .2471956{col 41}{space 1}   14.26{col 50}{space 3}0.000{col 58}{space 4} 3.040636{col 71}{space 3} 4.009625
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50136622
         {txt}sigma_e {c |} {res} 1.4325763
             {txt}rho {c |} {res} .10911765{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    12,681
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     6,240

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0386                                         {txt}min = {res}         1
{txt}     between = {res}0.3018                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.2563                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  3524.95
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:6,240} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1000357{col 30}{space 2} .0225013{col 41}{space 1}    4.45{col 50}{space 3}0.000{col 58}{space 4} .0559339{col 71}{space 3} .1441376
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0034778{col 30}{space 2} .0003759{col 41}{space 1}   -9.25{col 50}{space 3}0.000{col 58}{space 4}-.0042144{col 71}{space 3}-.0027411
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0305144{col 30}{space 2} .0049399{col 41}{space 1}   -6.18{col 50}{space 3}0.000{col 58}{space 4}-.0401965{col 71}{space 3}-.0208324
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}   .24825{col 30}{space 2} .0696626{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .1117138{col 71}{space 3} .3847861
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0072945{col 30}{space 2} .0012239{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .0048958{col 71}{space 3} .0096932
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2695252{col 30}{space 2} .0529075{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .1658284{col 71}{space 3}  .373222
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1898552{col 30}{space 2} .0329559{col 41}{space 1}    5.76{col 50}{space 3}0.000{col 58}{space 4} .1252629{col 71}{space 3} .2544476
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0280703{col 30}{space 2} .0523998{col 41}{space 1}    0.54{col 50}{space 3}0.592{col 58}{space 4}-.0746314{col 71}{space 3}  .130772
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1207483{col 30}{space 2} .0461508{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0302943{col 71}{space 3} .2112023
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0592671{col 30}{space 2} .0914439{col 41}{space 1}   -0.65{col 50}{space 3}0.517{col 58}{space 4}-.2384938{col 71}{space 3} .1199596
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1682034{col 30}{space 2} .0751249{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0209613{col 71}{space 3} .3154456
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2813184{col 30}{space 2} .0492186{col 41}{space 1}    5.72{col 50}{space 3}0.000{col 58}{space 4} .1848519{col 71}{space 3}  .377785
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1111243{col 30}{space 2} .0580985{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0027466{col 71}{space 3} .2249952
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0058647{col 30}{space 2} .0061948{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.0180062{col 71}{space 3} .0062769
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2594395{col 30}{space 2} .0611939{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .1395016{col 71}{space 3} .3793774
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1513147{col 30}{space 2} .0604036{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0329259{col 71}{space 3} .2697036
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7271188{col 30}{space 2}  .063837{col 41}{space 1}   11.39{col 50}{space 3}0.000{col 58}{space 4} .6020005{col 71}{space 3} .8522371
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8242045{col 30}{space 2} .0684953{col 41}{space 1}   12.03{col 50}{space 3}0.000{col 58}{space 4} .6899563{col 71}{space 3} .9584528
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1078942{col 30}{space 2} .0856693{col 41}{space 1}    1.26{col 50}{space 3}0.208{col 58}{space 4}-.0600144{col 71}{space 3} .2758029
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0667205{col 30}{space 2} .0594461{col 41}{space 1}   -1.12{col 50}{space 3}0.262{col 58}{space 4}-.1832328{col 71}{space 3} .0497918
{txt}{space 13}imr {c |}{col 18}{res}{space 2} .3003981{col 30}{space 2} .1583401{col 41}{space 1}    1.90{col 50}{space 3}0.058{col 58}{space 4}-.0099429{col 71}{space 3}  .610739
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0758715{col 30}{space 2}   .03049{col 41}{space 1}   -2.49{col 50}{space 3}0.013{col 58}{space 4}-.1356307{col 71}{space 3}-.0161123
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.6625998{col 30}{space 2} .0552126{col 41}{space 1}  -12.00{col 50}{space 3}0.000{col 58}{space 4}-.7708145{col 71}{space 3} -.554385
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.6257445{col 30}{space 2} .0543085{col 41}{space 1}  -11.52{col 50}{space 3}0.000{col 58}{space 4}-.7321873{col 71}{space 3}-.5193017
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.4657441{col 30}{space 2} .0516362{col 41}{space 1}   -9.02{col 50}{space 3}0.000{col 58}{space 4}-.5669493{col 71}{space 3}-.3645389
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.706808{col 30}{space 2} .1923237{col 41}{space 1}   24.47{col 50}{space 3}0.000{col 58}{space 4}  4.32986{col 71}{space 3} 5.083755
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84032585
         {txt}sigma_e {c |} {res} 1.2176775
             {txt}rho {c |} {res} .32260591{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,533
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,985

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0145                                         {txt}min = {res}         1
{txt}     between = {res}0.2229                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1663                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}25{txt})     =  {res}  1609.65
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,985} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0177173{col 30}{space 2} .0282524{col 41}{space 1}   -0.63{col 50}{space 3}0.531{col 58}{space 4}-.0730909{col 71}{space 3} .0376563
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0000866{col 30}{space 2} .0011354{col 41}{space 1}   -0.08{col 50}{space 3}0.939{col 58}{space 4}-.0023119{col 71}{space 3} .0021388
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0019503{col 30}{space 2}  .005465{col 41}{space 1}   -0.36{col 50}{space 3}0.721{col 58}{space 4}-.0126615{col 71}{space 3} .0087608
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .204196{col 30}{space 2}  .076825{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0536217{col 71}{space 3} .3547702
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0036178{col 30}{space 2}  .001262{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0011442{col 71}{space 3} .0060913
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1744304{col 30}{space 2} .0475023{col 41}{space 1}   -3.67{col 50}{space 3}0.000{col 58}{space 4}-.2675331{col 71}{space 3}-.0813276
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1719775{col 30}{space 2}  .038514{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .0964914{col 71}{space 3} .2474636
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .4289735{col 30}{space 2} .0971578{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .2385478{col 71}{space 3} .6193993
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1991245{col 30}{space 2} .0513859{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0984101{col 71}{space 3}  .299839
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.3777681{col 30}{space 2} .0823925{col 41}{space 1}   -4.58{col 50}{space 3}0.000{col 58}{space 4}-.5392546{col 71}{space 3}-.2162817
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0461009{col 30}{space 2} .0487445{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.1416383{col 71}{space 3} .0494365
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .112455{col 30}{space 2} .0448952{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .0244621{col 71}{space 3}  .200448
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1316717{col 30}{space 2} .0536368{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0265455{col 71}{space 3} .2367979
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0029633{col 30}{space 2} .0030569{col 41}{space 1}    0.97{col 50}{space 3}0.332{col 58}{space 4}-.0030282{col 71}{space 3} .0089547
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1415014{col 30}{space 2} .0327343{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0773433{col 71}{space 3} .2056594
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .322265{col 30}{space 2} .1220504{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0830506{col 71}{space 3} .5614795
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4286307{col 30}{space 2} .0685047{col 41}{space 1}    6.26{col 50}{space 3}0.000{col 58}{space 4} .2943638{col 71}{space 3} .5628975
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4129227{col 30}{space 2} .0805458{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .2550559{col 71}{space 3} .5707895
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0591858{col 30}{space 2} .0579312{col 41}{space 1}   -1.02{col 50}{space 3}0.307{col 58}{space 4} -.172729{col 71}{space 3} .0543573
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2712766{col 30}{space 2} .0600609{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .1535593{col 71}{space 3} .3889938
{txt}{space 13}imr {c |}{col 18}{res}{space 2} 1.149252{col 30}{space 2} .1602741{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .8351202{col 71}{space 3} 1.463383
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}  .067785{col 30}{space 2} .0370307{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0047938{col 71}{space 3} .1403637
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0637704{col 30}{space 2} .0406637{col 41}{space 1}   -1.57{col 50}{space 3}0.117{col 58}{space 4}-.1434698{col 71}{space 3} .0159289
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0204718{col 30}{space 2} .0355291{col 41}{space 1}   -0.58{col 50}{space 3}0.564{col 58}{space 4}-.0901076{col 71}{space 3}  .049164
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1267605{col 30}{space 2} .0436143{col 41}{space 1}   -2.91{col 50}{space 3}0.004{col 58}{space 4}-.2122429{col 71}{space 3}-.0412781
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.957675{col 30}{space 2} .1913168{col 41}{space 1}   20.69{col 50}{space 3}0.000{col 58}{space 4} 3.582701{col 71}{space 3} 4.332649
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .74944964
         {txt}sigma_e {c |} {res} 1.2120288
             {txt}rho {c |} {res} .27659324{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    14,609
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,947

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0462                                         {txt}min = {res}         1
{txt}     between = {res}0.2855                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1862                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}27{txt})     =  {res}  2176.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,947} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0218047{col 30}{space 2} .0175926{col 41}{space 1}    1.24{col 50}{space 3}0.215{col 58}{space 4}-.0126762{col 71}{space 3} .0562856
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0008737{col 30}{space 2} .0009883{col 41}{space 1}   -0.88{col 50}{space 3}0.377{col 58}{space 4}-.0028108{col 71}{space 3} .0010633
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0220474{col 30}{space 2} .0056418{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0109897{col 71}{space 3}  .033105
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1419579{col 30}{space 2} .0648956{col 41}{space 1}   -2.19{col 50}{space 3}0.029{col 58}{space 4}-.2691509{col 71}{space 3}-.0147649
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025066{col 30}{space 2} .0011435{col 41}{space 1}   -2.19{col 50}{space 3}0.028{col 58}{space 4}-.0047479{col 71}{space 3}-.0002654
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1411338{col 30}{space 2} .0395062{col 41}{space 1}    3.57{col 50}{space 3}0.000{col 58}{space 4}  .063703{col 71}{space 3} .2185646
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3883975{col 30}{space 2} .0358242{col 41}{space 1}   10.84{col 50}{space 3}0.000{col 58}{space 4} .3181834{col 71}{space 3} .4586117
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0956807{col 30}{space 2} .0607795{col 41}{space 1}    1.57{col 50}{space 3}0.115{col 58}{space 4}-.0234449{col 71}{space 3} .2148064
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2721348{col 30}{space 2} .0385941{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .1964917{col 71}{space 3} .3477779
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5973771{col 30}{space 2}   .05323{col 41}{space 1}   11.22{col 50}{space 3}0.000{col 58}{space 4} .4930482{col 71}{space 3}  .701706
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1457985{col 30}{space 2} .0353229{col 41}{space 1}    4.13{col 50}{space 3}0.000{col 58}{space 4} .0765669{col 71}{space 3} .2150302
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2581378{col 30}{space 2} .0341099{col 41}{space 1}    7.57{col 50}{space 3}0.000{col 58}{space 4} .1912837{col 71}{space 3}  .324992
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1142113{col 30}{space 2} .0330572{col 41}{space 1}   -3.45{col 50}{space 3}0.001{col 58}{space 4}-.1790022{col 71}{space 3}-.0494203
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0032541{col 30}{space 2} .0018649{col 41}{space 1}    1.74{col 50}{space 3}0.081{col 58}{space 4} -.000401{col 71}{space 3} .0069092
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0438048{col 30}{space 2}  .028065{col 41}{space 1}    1.56{col 50}{space 3}0.119{col 58}{space 4}-.0112016{col 71}{space 3} .0988113
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1656459{col 30}{space 2} .0889435{col 41}{space 1}    1.86{col 50}{space 3}0.063{col 58}{space 4}-.0086801{col 71}{space 3} .3399718
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3504455{col 30}{space 2} .0641841{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .2246469{col 71}{space 3}  .476244
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2519236{col 30}{space 2} .0731239{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .1086034{col 71}{space 3} .3952438
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1045875{col 30}{space 2} .0578281{col 41}{space 1}    1.81{col 50}{space 3}0.071{col 58}{space 4}-.0087535{col 71}{space 3} .2179285
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2749992{col 30}{space 2} .0555948{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1660354{col 71}{space 3} .3839629
{txt}{space 13}imr {c |}{col 18}{res}{space 2} -.869476{col 30}{space 2}  .133972{col 41}{space 1}   -6.49{col 50}{space 3}0.000{col 58}{space 4}-1.132056{col 71}{space 3}-.6068957
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .2427284{col 30}{space 2} .0317378{col 41}{space 1}    7.65{col 50}{space 3}0.000{col 58}{space 4} .1805234{col 71}{space 3} .3049333
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1305148{col 30}{space 2} .0404126{col 41}{space 1}   -3.23{col 50}{space 3}0.001{col 58}{space 4} -.209722{col 71}{space 3}-.0513075
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0087179{col 30}{space 2} .0377033{col 41}{space 1}    0.23{col 50}{space 3}0.817{col 58}{space 4}-.0651792{col 71}{space 3} .0826149
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .370222{col 30}{space 2} .0358453{col 41}{space 1}   10.33{col 50}{space 3}0.000{col 58}{space 4} .2999664{col 71}{space 3} .4404775
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1279815{col 30}{space 2} .0360438{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0573369{col 71}{space 3} .1986261
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2176273{col 30}{space 2} .0346735{col 41}{space 1}    6.28{col 50}{space 3}0.000{col 58}{space 4} .1496684{col 71}{space 3} .2855862
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.652841{col 30}{space 2} .1968837{col 41}{space 1}   13.47{col 50}{space 3}0.000{col 58}{space 4} 2.266956{col 71}{space 3} 3.038726
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7652415
         {txt}sigma_e {c |} {res}  1.247198
             {txt}rho {c |} {res} .27350207{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S18_farmer_imr.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist _cons)
{res}{txt}(note: file S18_farmer_imr.rtf not found)
(output written to {browse  `"S18_farmer_imr.rtf"'})

{com}. restore
{txt}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S11_S18_farmer_sample.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Apr 2024, 11:06:22
{txt}{.-}
{smcl}
{txt}{sf}{ul off}